Balancing Control Method, Device, Equipment and Storage Medium of a Wheeled-Legged Robot

Abstract

A balance control method, device, equipment and storage medium for a wheel-leg robot, relating to the technical field of robots. Simplify the wheel-leg robot into an n-order inverted pendulum model, including: wheels, n connecting rods and n rotating joints. The first connecting rod is an equivalent connecting rod corresponding to at least two leg mechanisms of the wheel-leg robot, and the wheel is an equivalent moving wheel corresponding to the moving wheels respectively connected by at least two leg mechanisms. The method includes: obtaining the actual state quantity of the wheel-leg robot at the first moment; processing the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment; establishing a sliding mode surface according to the equivalent state quantity at the first moment; determining the force and torque commands for the wheel-leg robot according to the sliding mode surface, the equivalent state quantity at the first moment and the dynamic equation; at the second moment, controlling the n rotating joints according to the force and torque commands. Realize the adjustable attitude of the n connecting rods, which helps to improve the robustness of the balance control.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and particularly relates to a balance control method, device, equipment and storage medium for a wheel-leg robot. Background Art

[0002] With the continuous development of robot technology, a wheel-leg robot has emerged in which a mobile wheel and a leg mechanism are connected by a joint. This wheel-leg robot combines the moving advantages of a wheeled robot and a legged robot, and has a motion mode of alternately striding forward through the leg mechanism.

[0003] In related technologies, in order to improve the balance ability of a wheel-leg robot during movement, the leg mechanism and the torso mechanism of the wheel-leg robot are regarded as a whole, the rotational torque of the joint motor between the mobile wheel and the leg mechanism is calculated, and the angle between the mobile wheel and the leg mechanism is changed by the rotation of the joint motor to maintain the balance ability of the wheel-leg robot.

[0004] However, the application scenarios of the balance control process in related technologies are few, and the robustness of the balance control method for a wheel-leg robot in different motion states needs to be further improved. Summary of the Invention

[0005] Embodiments of the present application provide a balance control method, device, equipment and storage medium for a wheel-leg robot. The technical solutions are as follows:

[0006] According to one aspect of the embodiments of the present application, a balance control method for a wheel-leg robot is provided. The wheel-leg robot is simplified into an n-order inverted pendulum model, and the n-order inverted pendulum model includes: a wheel, n linkages and n rotating joints. The wheel and the first linkage among the n linkages are connected by the first rotating joint among the n rotating joints. The n linkages are serially connected by n - 1 rotating joints except the first rotating joint. The first linkage is an equivalent linkage corresponding to at least two leg mechanisms of the wheel-leg robot, and the wheel is an equivalent mobile wheel corresponding to the mobile wheels respectively connected by the at least two leg mechanisms. n is a positive integer greater than or equal to 2. The method includes:

[0007] Obtain the actual state quantity of the wheel-leg robot at a first moment, where the actual state quantity is used to characterize the motion states of n - 1 linkages, the at least two leg mechanisms and at least two of the mobile wheels. The n - 1 linkages are other linkages among the n linkages except the first linkage.

[0008] Process the actual state quantity at the first moment to obtain an equivalent state quantity at the first moment, where the equivalent state quantity is used to characterize the motion states of the n linkages and the wheel.

[0009] Based on the equivalent state quantity at the first moment, a sliding mode surface is established, and the equivalent state quantity gradually approaches 0 on the sliding mode surface;

[0010] Based on the sliding mode surface, the equivalent state quantity at the first moment, and the dynamic equation of the wheel-legged robot, force and torque commands for the whole-body joints of the wheel-legged robot are determined. The whole-body joints include the n rotational joints, and the dynamic equation is established based on the nth-order inverted pendulum model;

[0011] At the second moment, the n rotational joints are controlled according to the force and torque commands of the whole-body joints.

[0012] According to one aspect of the embodiments of the present application, a balance control device for a wheel-legged robot is provided. The wheel-legged robot is simplified to an nth-order inverted pendulum model. The nth-order inverted pendulum model includes: a wheel, n linkages, and n rotational joints. The wheel and the first linkage among the n linkages are connected through the first rotational joint among the n rotational joints. The n linkages are serially connected through n - 1 rotational joints except the first rotational joint. The first linkage is an equivalent linkage corresponding to at least two leg mechanisms of the wheel-legged robot, and the wheel is an equivalent moving wheel corresponding to the moving wheels respectively connected by the at least two leg mechanisms. n is a positive integer greater than or equal to 2. The method includes:

[0013] A state quantity acquisition module is configured to acquire the actual state quantity of the wheel-legged robot at the first moment. The actual state quantity is used to characterize the motion states of n - 1 linkages, the at least two leg mechanisms, and at least two of the moving wheels. The n - 1 linkages are the other linkages among the n linkages except the first linkage;

[0014] A state quantity processing module is configured to process the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment. The equivalent state quantity is used to characterize the motion states of the n linkages and the wheel;

[0015] A sliding mode surface establishment module is configured to establish a sliding mode surface according to the equivalent state quantity at the first moment, and the equivalent state quantity gradually approaches 0 on the sliding mode surface;

[0016] An instruction determination module is configured to determine force and torque commands for the whole-body joints of the wheel-legged robot according to the sliding mode surface, the equivalent state quantity at the first moment, and the dynamic equation of the wheel-legged robot. The whole-body joints include the n rotational joints, and the dynamic equation is established based on the nth-order inverted pendulum model;

[0017] The joint control module is used to control the n rotating joints according to the force and torque commands of the whole body joints at the second moment.

[0018] According to one aspect of the embodiments of the present application, a computer device is provided. The computer device includes a processor and a memory. A computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the above-mentioned balance control method for the wheel-legged robot.

[0019] According to one aspect of the embodiments of the present application, a computer-readable storage medium is provided. A computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by a processor to implement the above-mentioned balance control method for the wheel-legged robot.

[0020] According to one aspect of the embodiments of the present application, a computer program product is provided. The computer program product includes a computer program, and the computer program is loaded and executed by a processor to implement the above-mentioned balance control method for the wheel-legged robot.

[0021] The technical solutions provided by the embodiments of the present application can bring the following beneficial effects:

[0022] On the one hand, based on abstracting the wheel-legged robot into an n-order inverted pendulum model, the balance control under multiple wheel motion modes can be realized. During the balance control process, the deflection angles of multiple linkages in the wheel-legged robot are adjusted to change the posture of the wheel-legged robot; making the postures of multiple linkages in the wheel-legged robot variable during the balance adjustment process greatly enriches the robot postures, helps to quickly adjust the robot to the balanced state, and also helps to improve the ability of the robot to return to the balanced state under the action of different disturbing forces, and improves the robustness of the robot balance control process.

[0023] On the other hand, using the method provided by the present application to determine the equivalent state quantity according to the actual state quantity enables the balance control under multiple wheel motion modes to share a set of control parameters with the balance control under two-wheel motion modes. After the wheel-legged robot switches the motion mode, it is not necessary to adjust the control parameters in the controller (such as a robust controller) for balance control, which helps to improve the versatility of the controller. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a schematic diagram of the implementation environment of the solution provided by an embodiment of the present application;

[0025] Figure 2 is a schematic diagram of a quadruped wheel-legged robot provided by an embodiment of the present application;

[0026] Figure 3It is a schematic diagram of a quadruped wheel-leg robot provided by an embodiment of the present application;

[0027] Figure 4 It is a schematic diagram of the quadruped wheel-leg robot in the double-wheel mode provided by an embodiment of the present application;

[0028] Figure 5 It is a schematic diagram of the quadruped wheel-leg robot climbing stairs provided by an embodiment of the present application;

[0029] Figure 6 It is a schematic diagram of the planar movement of the robot when climbing stairs provided by an embodiment of the present application;

[0030] Figure 7 It is a schematic diagram of the movement sequence of the robot going up and down stairs provided by an embodiment of the present application;

[0031] Figure 8 It is a block diagram of the robot control system provided by an embodiment of the present application;

[0032] Figure 9 It is a schematic diagram of the four-wheel motion mode of the wheel-leg robot provided by an embodiment of the present application;

[0033] Figure 10 It is a schematic diagram of the simplified dynamic model provided by an embodiment of the present application;

[0034] Figure 11 It is a schematic diagram of the second-order inverted pendulum provided by an embodiment of the present application;

[0035] Figure 12 It is a schematic diagram of the second-order inverted pendulum provided by an embodiment of the present application;

[0036] Figure 13 It is a flowchart of the balance control method of the wheel-leg robot provided by an embodiment of the present application;

[0037] Figure 14 It is a schematic diagram of the inverted pendulum related to the center of mass provided by an embodiment of the present application;

[0038] Figure 15 It is a simulation schematic diagram of the multi-wheel balance control method provided by an embodiment of the present application;

[0039] Figure 16 It is a block diagram of the balance control device of the wheel-leg robot provided by an embodiment of the present application;

[0040] Figure 17 It is a block diagram of the structure of the computer device provided by an embodiment of the present application. Detailed implementation manners

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the following will further describe the embodiments of this application in detail with reference to the accompanying drawings.

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following will further describe the embodiments of this application in detail with reference to the accompanying drawings.

[0043] Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a way similar to human intelligence. Artificial intelligence also studies the design principles and implementation methods of various intelligent machines, enabling the machines to have the functions of perception, reasoning, and decision-making.

[0044] Artificial intelligence technology is an interdisciplinary subject with a wide range of fields, including both hardware-level technologies and software-level technologies. The basic technologies of artificial intelligence generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. The software technologies of artificial intelligence mainly include several major directions such as computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0045] The technical solution provided in the embodiments of this application mainly relates to robotics in artificial intelligence technology, and mainly relates to robot intelligent control. A robot is a mechatronic device that combines mechanical transmission and modern microelectronics technology and can imitate a certain skill of a human. Robots are developed on the basis of electronics, machinery, and information technology. A robot does not necessarily have to look like a human. As long as it can autonomously complete the tasks and commands given by humans, it belongs to the members of the robot family. A robot is an automated machine that has some intelligent capabilities similar to humans or living organisms, such as perception capabilities, planning capabilities, action capabilities, and cooperation capabilities, and is an automated machine with high flexibility. With the development of computer technology and artificial intelligence technology, robots have been greatly improved in terms of function and technology level. Mobile robots and technologies such as robot vision and touch are typical representatives.

[0046] For the technical solution provided in the embodiments of this application, the execution subject of each step can be a computer device, which refers to an electronic device with data calculation, processing, and storage capabilities.

[0047] Optionally, the computer device may be a PC (Personal Computer) device such as a desktop computer or a laptop computer for controlling a robot; it may also be a server for controlling a robot. Among them, the server may be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The computer device and the robot may be connected through physical lines, networks, etc. For example, for reference Figure 1 , the computer device 101 may determine the equivalent state quantity corresponding to the n-order inverted pendulum model abstracted from the robot according to the current actual state quantity of the robot 103, and gradually calculate the force and torque commands of the whole body joints of the robot according to the equivalent state quantity, and control the n rotating joints included in the robot 103 according to the force and torque commands of the whole body joints of the robot, so that the robot 103 maintains or restores the balance state.

[0048] Optionally, the computer device may also be the robot itself, that is, the execution subject of each step in the technical solution provided by the embodiments of the present application is the robot or other devices in communication connection with the robot. For example, for reference Figure 1 , the computer device 101 may send the state quantity of the robot 103 at the first moment to the robot 103 through the network 102. The robot 103 gradually calculates the force and torque commands of the whole body joints of the robot according to the equivalent state quantity at the first moment, and controls the movement of the rotation motors of the n rotating joints through the force and torque commands of the whole body joints of the robot, and adjusts the posture of the robot 103 to change the balance state of the robot.

[0049] The robot in the embodiments of the present application may refer to a wheel-legged robot, a leg-footed robot, etc. A wheel-legged robot refers to a robot with both a wheeled structure and a legged mechanism, and a leg-footed robot refers to a robot with feet as its feet. The embodiments of the present application do not limit this.

[0050] In one example, the robot 103 may include at least 2 moving wheels. Optionally, the balance control method provided by the present application is applicable when j moving wheels are disengaged from the contact surface and, when viewed from the side of the wheel-legged robot, the j moving wheels do not overlap. For specific content related to this process, please refer to the following introduction. For each of the at least 2 moving wheels, the moving wheel is connected to its corresponding leg mechanism through a first rotating joint. For example, the robot 103 has 2 moving wheels, and the robot 103 moves by rolling through the 2 moving wheels. Another example is that the robot 103 has four moving wheels. Exemplarily, each moving wheel is connected to its corresponding leg mechanism through a first rotating joint. Exemplarily, different moving wheels are respectively connected to different leg mechanisms.

[0051] In some embodiments, the robot in the embodiments of the present application includes moving wheels and at least two linkages. The wheel-legged robot consists of at least one mechanism part, and each mechanism part can be simplified into a linkage. The above-mentioned at least two linkages can both be equivalent to the linkages in an n-order inverted pendulum model; that is, in the method provided in the present application, during the balance control process, the wheel-legged robot is simplified into an n-stage inverted pendulum model. The n-order inverted pendulum model includes wheels and n linkages. The n linkages are serially connected through n - 1 rotating joints. The first linkage in the n mechanisms is connected to the moving wheel through the first rotating joint, where the wheel refers to an equivalent moving wheel obtained based on at least two moving wheels, and the first linkage refers to an equivalent leg mechanism obtained by equivalent of at least two leg mechanisms in the wheel-legged robot.

[0052] The wheel-legged robot includes at least two leg mechanisms. Any one of the leg mechanisms in at least one leg mechanism has a corresponding moving wheel. For example, leg mechanism 1 corresponds to moving wheel 1, and leg mechanism 1 is connected to moving wheel 1 through a real rotating joint 1. That is, the number of leg mechanisms of the wheel-legged robot is equal to the number of moving wheels.

[0053] Optionally, at least two leg mechanisms can be divided into an outer leg group and an inner leg group. The outer leg group includes at least two leg mechanisms, and the inner leg group includes at least one leg mechanism.

[0054] Exemplarily, taking the wheel-legged robot as an example, the robot in the embodiments of the present application is described.

[0055] At least one leg mechanism is divided into: an outer leg mechanism and an inner leg mechanism; wherein, the outer leg mechanism includes: at least two leg mechanisms, and the inner leg mechanism can also include at least two leg mechanisms. Among the outer leg mechanisms, at least two leg mechanisms are respectively located on both sides of the central axis (i.e., the sagittal plane) of the wheel-legged robot. Among the inner leg mechanisms, at least two leg mechanisms are respectively located on both sides of the central axis of the wheel-legged robot. The rotation centers of the hip joints corresponding to the outer leg mechanism and the inner leg mechanism, that is, the outer leg and the inner leg mechanism, are located in the same vertical plane.

[0056] Exemplarily, the wheel-legged robot is a quadruped wheel-legged robot, that is, the wheel-legged robot includes two outer leg mechanisms and two inner leg mechanisms; the wheel-legged robot is also a tripod wheel-legged robot, that is, the wheel-legged robot includes two outer leg mechanisms and one inner leg mechanism. Among them, the hip joint corresponding to at least one inner leg mechanism in the inner leg mechanism group is located between the hip joints corresponding to the two outer leg mechanisms in the outer leg mechanism group, and the rotation centers of the hip joints corresponding to the outer leg mechanisms and the rotation centers of the hip joints corresponding to the inner leg mechanism are located in the same vertical plane. The wheel-legged robot can stand on the support surface through the outer leg mechanism or the inner leg mechanism, and the wheel-legged robot can also slide on the support surface through the wheels on the outer leg mechanism or the wheels on the inner leg mechanism. It can also move (i.e., walk) on the support surface by controlling the alternating swing of the outer leg mechanism group and the inner leg mechanism group.

[0057] Exemplarily, as Figure 2 shown, it exemplarily shows a schematic structural diagram of a quadruped wheel-legged robot. The quadruped wheel-legged robot 200 may include: a torso structure, a leg mechanism, and a moving wheel.

[0058] Among them, the quadruped wheel-legged robot 200 has four leg mechanisms: 2 outer leg mechanisms 201 (i.e., the first leg mechanism group) and 2 inner leg mechanisms 202 (i.e., the second leg mechanism group). The 2 inner leg mechanisms 202 are located between the 2 outer leg mechanisms 201. All four leg mechanisms can be individually telescoped in the direction shown in the figure. A wheel 203 is installed at the end of each of the four leg mechanisms, and each wheel 203 can be individually driven. The quadruped wheel-legged robot 200 can stand through the 2 inner leg mechanisms 202 or the 2 outer leg mechanisms 201 to be in a two-wheel support state; the quadruped wheel-legged robot 200 can also stand through the 2 inner leg mechanisms 202 and the 2 outer leg mechanisms 201 at the same time to be in a four-wheel support state. The embodiments of the present application do not limit this.

[0059] Optionally, the 2 inner leg mechanisms 202 can be implemented as a whole, that is, the quadruped wheel-legged robot 200 can be implemented as a tripod wheel-legged robot, which only has one inner leg mechanism.

[0060] Another end of each of the four leg mechanisms is connected to a hip joint 204 respectively. Each leg mechanism can rotate around its respective hip joint 204 and maintain linkage. In the embodiments of the present application, the rotation centers of the respective hip joints 204 corresponding to the quadruped wheel-legged robot 200 are located in the same vertical plane 205, and the rotation planes of the respective leg mechanisms corresponding to the quadruped wheel-legged robot 200 are parallel. The hip joints 204 corresponding to the two inner leg mechanisms 202 are located between the hip joints 204 corresponding to the two outer leg mechanisms 201.

[0061] Optionally, the respective hip joints 204 corresponding to the quadruped wheel-legged robot 200 may be coaxial, that is, the rotation centers of the respective hip joints 204 are located on the same straight line. The respective hip joints 204 corresponding to the quadruped wheel-legged robot 200 may also be non-coaxial. For example, the hip joints 204 corresponding to the two inner leg mechanisms 202 are coaxial, and the hip joints 204 corresponding to the two outer leg mechanisms 201 are coaxial, but the hip joints 204 corresponding to the two inner leg mechanisms 202 are non-coaxial with the hip joints 204 corresponding to the two outer leg mechanisms 201. The hip joint 204 may be used as the rotation joint connected to the first link among the n rotation joints in the embodiments of the present application. One end of the first link is connected to the actual rotation joint, and the other end is connected to the hip joint 204.

[0062] Optionally, the hip joints 204 corresponding to the two outer leg mechanisms 201 share a driving motor to enable the two outer leg mechanisms 201 to move synchronously; the hip joints 204 corresponding to the two inner leg mechanisms 202 share a driving motor to enable the two inner leg mechanisms 202 to move synchronously. In a feasible example, the respective hip joints 204 corresponding to the quadruped wheel-legged robot 200 may also be independently driven by their respective corresponding driving motors, and the embodiments of the present application do not limit this.

[0063] The fuselage of the quadruped wheel-legged robot 200 may include a waist 206, a body 207, an upper limb 208, and a head 209.

[0064] Among them, the respective hip joints 204 corresponding to the quadruped wheel-legged robot 200 are connected to the same end of the waist 206, and the other end of the waist 206 is connected to one end of the body (trunk mechanism) 207. The waist 206 has two rotation centers: a pitch rotation center that can enable the body 207 to perform pitching, and a yaw rotation center that can enable the body 207 to perform yaw. The yaw rotation center and the pitch rotation center are designed in series and are located at the upper end of the pitch rotation center and are connected to the body 207.

[0065] Exemplarily, if Figure 2 the body 207 in rotates 90 degrees along the yaw rotation center, the robot will change from Figure 2 to Figure 3 the robot shown.

[0066] The other end of the body 207 is connected to the upper limb (robotic arm link) 208 and the head 209. The upper limb 208 can be a multi-degree-of-freedom upper limb. In some embodiments, an end effector, such as a robotic gripper, a suction cup, etc., is deployed on the upper limb 208. A data acquisition device can be deployed in the head 209 to sense the real environment, such as an image acquisition device, a video shooting device, an IMU (Inertial Measurement Unit), etc. Among them, the IMU can be arranged at the geometric center of the body 207, the center point of the hip joint (i.e., the rotation center of the hip joint), etc., and it can be used to measure the actual acceleration, actual attitude angular velocity, actual Euler angle, etc. of the body 207.

[0067] In the technical solution provided by the embodiments of the present application, the moving wheels, leg mechanisms, hip joints, waist, and torso mechanisms (including IMUs) of the quadruped wheel-legged robot 200 are essential hardware for the control algorithm, and the rest are non-essential hardware.

[0068] The quadruped wheel-legged robot has a more stable structure than the biped wheel-legged robot, has a stronger ability to resist external impact disturbances, has fewer redundant joints than the hexapod wheel-legged robot, has a low design complexity, can not only carry large loads, but also pass through narrow spaces, and can also perform tasks on objects of different heights. The quadruped wheel-legged robot has a strong adaptability to the environment.

[0069] The balance control method for the wheel-legged robot provided by the embodiments of the present application is applicable to various scenarios, such as the balance of the wheel-legged robot during movement, the balance of the wheel-legged robot under external force disturbances, etc. The balance control method for the wheel-legged robot provided by the embodiments of the present application can flexibly control the rotation of multiple joints of the wheel-legged robot during the balance control process, enrich the posture of the robot during the balance control process, and help the robot quickly reach a balanced state.

[0070] When moving on flat ground, the robot can maintain the four-wheel motion mode as shown in Figure 2 , or can form a two-wheel dynamic smooth motion mode as shown in Figure 4 through the rotation center of the hip joint. In the four-wheel motion mode, the robot is always in a stable state (not falling), which is convenient for the upper limb to follow the operation instructions to perform some operation tasks. However, when moving on flat ground, switching from the four-wheel motion mode to the two-wheel motion mode can reduce the floor area of the robot and match the biped robot. When moving on non-flat ground, such as when the robot climbs stairs or crosses a threshold, etc., it can perform dynamic obstacle crossing through the two-wheel alternating mode as shown in Figure 5 .

[0071] In some embodiments, referring to Figure 5, when the wheel-legged robot 501 needs to climb stairs, it can first construct an objective function corresponding to the stair-climbing task according to the stair-climbing task to be performed, and then control the outer leg mechanism group 502 (i.e., the first leg mechanism group) and the inner leg mechanism group 503 (i.e., the second leg mechanism group) of the robot 501 to swing alternately according to the joint torque information of the robot 501 when the value of the objective function is minimized, so as to perform the stair-climbing task. For example, first use the outer leg mechanism group 502 as the supporting leg mechanism group and the inner leg mechanism group 503 as the swinging leg mechanism group to make the robot 501 climb the first step, and then use the inner leg mechanism group 503 as the supporting leg mechanism group and the outer leg mechanism group 502 as the swinging leg mechanism group to make the robot 501 climb the second step. The outer leg mechanism group 502 and the inner leg mechanism group 503 swing alternately in sequence to complete the stair-climbing task.

[0072] Figure 6 It is a schematic diagram of the planar movement of the robot when climbing stairs provided by an exemplary embodiment of the present application. Figure 6 In [the figure], the left leg mechanism and the right leg mechanism of the robot completely overlap. Therefore, Figure 6 In [the figure], the leg mechanisms respectively connected to the two wheels of the robot represent the first leg mechanism and the second leg mechanism of the robot. Considering the specific form during the stair-climbing process, Figure 6 The robot shown in [the figure] will not touch the same support surface at the same time in the posture where the wheels are on the ground, so as to conform to the actual stair-climbing motion state. The movement stage of the robot during the entire movement process can also be divided into a single-leg support phase (Single Support Phase, SSP) and a double-leg support phase (Double Support Phase, DSP).

[0073] Figure 6The first state shown is the single-leg support phase. The first leg mechanism 601 of the robot is in contact with the support surface, and the second leg mechanism 602 is not in contact with the support surface. The first leg mechanism 601 uses the joints of the wheels and the fuselage to cooperate in control to maintain the balance of the robot. In the first phase, the robot swings the second leg mechanism 602, gradually lifting it from the initial vertical downward gravity direction until it rests on the upper step, entering the second state, which is the double-leg support phase. During the first phase, the first leg mechanism 601 is the supporting wheel leg, and the second leg mechanism 602 is the swinging wheel leg. In the second phase, the robot always maintains two contact points between the wheels and the support surface in this plane. During this process, the robot changes the angles of the joints of the fuselage. On the premise of keeping the contact points of the two wheels with the support surface unchanged, it gradually moves the projection of the center of mass of the fuselage on the support surface from near the rear wheel center on the next step to near the front wheel center on the upper step, entering the third state, which is the double-leg support phase. In the third phase, the robot lifts the first leg mechanism 601 from the lower step and uses the second leg mechanism 602 to maintain the balance of the robot until the first leg mechanism 601 and the second leg mechanism 602 coincide vertically, entering the fourth state, which is the single-leg support phase. During the third phase, the second leg mechanism 602 is the supporting wheel leg, and the first leg mechanism 601 is the swinging wheel leg.

[0074] During the process of the robot moving up one more step, the supporting leg mechanism and the swinging leg structure will be interchanged. In the periodic movement of going up the stairs, the supporting leg mechanism and the swinging leg mechanism perform a periodic interchange movement process. Similarly, the stage division of the robot's task of going down the stairs is the same as that of the above-mentioned task of going up the stairs, except that the movement directions of each leg mechanism are opposite to those of each leg mechanism in the task of going up the stairs. Therefore, for the task of the robot going down the stairs, it will not be elaborated here. The specific process can be referred to Figure 7 the schematic diagram of the action sequence of the robot going up and down the stairs shown, without detailed description.

[0075] Please refer to Figure 8 , which shows the block diagram of the robot control system provided by an embodiment of the present application. The body of the robot can be referred to Figure 2 . The 4 moving wheels of the robot are individually driven by 4 rotary motors, and the lengths of the 4 moving leg mechanisms are individually driven by 4 linear motors. Usually, the driving modes of the linear motors of the 2 outer moving legs are the same, and the driving modes of the linear motors of the 2 inner moving legs are the same.

[0076] Optionally, the leg lengths of the two outer moving legs are equal, and the leg lengths of the two inner moving legs are equal. The changing speeds of the leg lengths of the two outer moving legs are equal, and the changing speeds of the leg lengths of the two inner moving legs are equal.

[0077] The two outer moving legs are driven by the same rotary motor, which is used to adjust the angle between the outer moving legs and the straight line L1 perpendicular to the contact surface direction, that is, the angles between the two outer moving legs and the straight line L1 are equal respectively. The two inner moving legs are driven by the same rotary motor, which is used to adjust the angle between the inner moving legs and L1, that is, the angles between the two inner moving legs and the straight line L1 are equal respectively.

[0078] In addition, rotary motors are respectively arranged at each joint of the torso mechanism of the wheel-leg robot, and the rotation of each joint can be actively driven by the rotary motor.

[0079] For all the above-mentioned rotary motors, the rotary motor can receive rotation angle instructions, rotation speed instructions, torque instructions, etc.; among them, the rotation angle instruction is used to indicate the rotation angle of the rotary motor, the rotation speed instruction is used to indicate the rotation speed and rotation direction of the rotary motor, and the torque is used to indicate the torque that needs to be achieved during the rotation of the rotary motor.

[0080] After the rotary motor receives any one of the above-mentioned rotation angle instructions, rotation speed instructions, and torque instructions, the underlying drive board of the rotary motor will drive the motor to rotate according to the received instruction signal, so as to drive each joint to move.

[0081] For all the above-mentioned linear motors, the linear motor can receive linear movement position instructions, linear movement speed instructions, driving force instructions, etc., and the underlying drive board of the linear motor will drive the motor to move linearly according to the received instruction signal, so as to drive the leg mechanism to move telescopically.

[0082] The rotation and movement of the rotary motor and the linear motor change the posture of the robot and the position of the robot in three-dimensional space, realizing the balance control of the wheel-leg robot. The rapidly changing joint angle instructions can also cause the posture of the robot to change dynamically, so as to change the contact situation between the robot and the environment.

[0083] Since the postures and states (such as motion states) of the wheel-leg robot are different at different times, it is necessary to collect the posture information and motion state information of the wheel-leg robot through the sensors arranged on the wheel-leg robot, so as to generate instruction signals to realize the balance control and motion state of the wheel-leg robot.

[0084] Optionally, the state of the wheel-leg robot can be obtained by different sensors installed on the wheel-leg robot body. The sensor types include at least one of the following:

[0085] The IMU sensor is used to determine the current posture of the wheel-leg robot, including the position information and posture information of the wheel-leg robot.

[0086] Motor encoder, which is used to determine the rotational speed of each joint of the wheel-legged robot in the current state, position information related to movement, and speed information of rotation and movement.

[0087] Force / torque sensor, which is used to determine the magnitude of the force on the joint where the force / torque sensor is located at the current moment, as well as the magnitude and direction of the torque.

[0088] Tactile sensor, which is used to determine the contact position between the moving wheel of the wheel-legged robot and the contact surface, the pressure magnitude on body parts such as the body surface, inside the hand, and fingertips, and the change characteristics of the pressure over a period of time.

[0089] Vision sensors (such as cameras, infrared sensors), which are used to identify obstacles that appear within the field of view of the wheel-legged robot, and are also used to determine the position information of the centroid of the wheel-legged robot and the speed information corresponding to the centroid of the wheel-legged robot.

[0090] Optionally, the control system of the wheel-legged robot includes the following control modules:

[0091] 1. State Estimation module, which is used to fuse the various attitude information and state information obtained by the wheel-legged robot. For example: fusing the current attitude of the wheel-legged robot obtained from the IMU sensor, the odometry information obtained from the rotation of the moving wheels, and the visual positioning information can obtain the position of the wheel-legged robot in the world coordinate system; fusing the information obtained from the force / torque sensor and the tactile sensor to obtain the contact situation between the robot and the external environment; fusing the current attitude of the wheel-legged robot obtained from the IMU sensor and the angle information of each motor joint encoder, and combining the model parameters of the wheel-legged robot itself, the centroid position of the wheel-legged robot can be estimated. These fused state information of the wheel-legged robot will be used as feedback quantities for the motion generation, planning, and control of the wheel-legged robot.

[0092] 2. Motion Generation module, which is used to adopt the motion generation strategy corresponding to the working mode according to the working mode when the wheel-legged robot completes an action. The working modes of this robot include but are not limited to: four-wheel motion mode, two-wheel motion mode, four-wheel to two-wheel conversion mode, up and down stairs mode, four-wheel active suspension mode (the four-wheel active suspension mode means that during the four-wheel mode driving process, the contact surface is uneven, and the robot relies on the four wheels to adjust the upper body posture to keep the upper body posture relatively stable), folding mode, etc. Considering the complexity of the upper body and the ability to complete various tasks, there are even more motion modes that the robot can include, which will not be listed one by one here.

[0093] In different modes, the way of action generation is different. Some common basic technologies and algorithm modules will be called in these modes, including but not limited to: model-free controllers, model-based controllers, etc. Model-based controllers such as: LQR (Linear Quadratic Regulator), MPC (Model Predictive Control), adaptive controllers, robust controllers, etc. Optionally, the robust controller in the embodiments of the present application is implemented based on sliding mode control, and the robust controller can also be called a sliding mode controller.

[0094] For example, when the wheel-legged robot needs to control the balance of the moving wheels in the two-wheel mode, the PID control (Proportional Integral Derivative Control) of the model-free controller can be used to generate the reference trajectories of the foot wheels and the center of mass of the robot. Exemplarily, the specific method is to call one or several of the model-free controller, model-based controllers (LQR, MPC, etc.), adaptive controllers, and robust controllers.

[0095] For another example, in the two-wheel control stage when the wheel-legged robot is in the four-wheel to two-wheel mode, the model-free controller, model-based controllers (LQR, MPC, etc.), adaptive controllers, and robust controllers can also be used to control the balance of the moving wheels.

[0096] For another example, when the wheel-legged robot is in the four-wheel mode, if the leg mechanisms that extend the wheel-legged robot forward and the leg mechanisms that extend backward are made equivalent to obtain an equivalent leg mechanism, and the first link obtained by this equivalence and other mechanisms in the wheel-legged robot can be simplified into an n-order inverted pendulum model, the control trajectory obtained by this method can keep the robot balanced in the four-wheel state. By this method, the wheel-legged robot can maintain the relative stability of its fuselage when the contact surface is uneven, there are potholes or obstacles. Exemplarily, when the wheel-legged robot is in the four-wheel active suspension mode, the above modules can also be used to control the relative stability of the fuselage of the wheel-legged robot.

[0097] The input of the action generation module is a series of task information of the wheel-legged robot. The types of task information include but not limited to: center of mass tasks, tasks of the supporting legs, tasks of the swinging legs, tasks of the waist, etc. Similarly, considering the complexity of the upper body of the wheel-legged robot, the upper body can independently complete various actions and tasks, and the types of task information can be more. They are not listed one by one here for the time being.

[0098] Exemplarily, these tasks can also be used as inputs to a Whole Body Controller (WBC) (also known as a whole body dynamics controller). In the whole body control module, a detailed model of the wheel-legged robot (obtaining the whole body dynamics model of the wheel-legged robot) and calibration are performed, and the whole body dynamics model of the wheel-legged robot and the external force conditions are used as optimization constraints. Through an optimization process, target joint angle commands, target joint angular velocity commands, target joint torque commands, etc. of at least one rotating joint of the wheel-legged robot are calculated. Finally, the whole body control module sends the determined target joint angle commands, target joint angular velocity commands, target joint torque commands, etc. to the drivers of each joint of the robot, thus completing the control loop of the wheel-legged robot.

[0099] The balance control method of the wheel-legged robot provided in this application is mainly completed by Figure 8 a robust controller in the control system. Optionally, the balance control method is jointly completed by a robust controller and a whole body control module. For the specific content of this process, please refer to the following embodiments.

[0100] Before introducing the specific steps of the balance control method provided in this application, in order to facilitate the understanding of the structure of the wheel-legged robot, the methods related to balance control in the wheel-legged robot are introduced and explained first.

[0101] Please refer to Figure 9 , which shows a schematic diagram of the four-wheel motion mode of the wheel-legged robot provided in an embodiment of this application. Observed from the side of the wheel-legged robot (i.e., the yoz plane in the world coordinate system), there are at least two moving wheels in the wheel-legged robot that do not coincide in the yoz plane, and the leg mechanisms respectively connected to the at least two moving wheels do not coincide in the yoz plane. That is to say, along the forward direction of the wheel-legged robot, there are at least two moving wheels that are in contact with the contact surface and do not coincide.

[0102] Optionally, the external leg mechanisms included in the external leg group of the wheel-legged robot do not coincide in the yoz plane with the internal leg mechanisms included in the internal leg group, at least two external leg mechanisms included in the external leg group coincide in the yoz plane, and at least one internal leg mechanism included in the internal leg group coincides in the yoz plane.

[0103] The wheel-legged robot also includes multiple parts that can be simplified into linkages, such as Figure 9 the n - 1 linkages shown, and the n - 1 linkages are serially connected through rotating joints.

[0104] Please refer to Figure 10, which shows a schematic diagram of a simplified dynamic model provided by an embodiment of the present application. As Figure 10 described above, by equating at least two non-coincident moving wheels 1012 and 1014 in the forward direction, the wheel 1016 in the n-order inverted pendulum model is obtained, and by equating at least two non-coincident leg mechanisms 1022 and 1024 in the forward direction, the first link 1026 in the n-order inverted pendulum model is obtained, enabling the wheeled-leg robot in the multi-wheel motion mode to be simplified into an n-order inverted pendulum model, and based on the n-order inverted pendulum model, the balance control of the wheeled-leg robot is carried out.

[0105] In some embodiments, the equivalent contact point between the wheel 1016 and the contact surface is located between the contact points of at least two non-coincident moving wheels 1012 and 1014 with the contact surface. Exemplarily, the equivalent contact point between the wheel 1016 and the contact surface is the midpoint of the line connecting the contact points of at least two non-coincident moving wheels 1012 and 1014 with the contact surface, and the at least two non-coincident moving wheels 1012 and 1014 are two moving wheels distributed on the same side of the axis of the wheeled-leg robot.

[0106] Figure 10 Only taking two non-coincident moving wheels in the forward direction as an example, it shows the method of equivalently obtaining the wheel and the first link, and establishing the corresponding n-order inverted pendulum model of the wheeled-leg robot in this posture; in the case where there are multiple non-coincident moving wheels in the forward direction in the wheeled-leg robot, the multiple moving wheels can also be equated to obtain the wheel; by equating multiple leg mechanisms, the obtained first link is used to simplify the wheeled-leg robot into an n-order inverted pendulum model for balance control of the wheeled-leg robot.

[0107] Before introducing the specific steps of the balance control method provided by the present application, first introduce the method for establishing the dynamic model corresponding to the balance control method provided by the present application. For the convenience of understanding the principle of the n-order inverted pendulum model involved in the present application, first introduce it from the second-order inverted pendulum model that is relatively easy to understand.

[0108] Please refer to Figure 11 , which shows a schematic diagram of a second-order inverted pendulum provided by an embodiment of the present application. From the content introduced above, it can be seen that after equating the non-coincident moving wheels and non-coincident leg mechanisms of the wheeled-leg robot, the wheeled-leg robot can be simplified into an n-order inverted pendulum model for balance control. Based on this, the dynamic equation of the wheeled-leg robot can be derived, which is convenient for subsequent realization of the balance control of the wheeled-leg robot.

[0109] For the sake of clear and concise narration and easy understanding, the case where n equals 2 is introduced. After equivalent transformation of at least two leg mechanisms and at least two mobile wheels, the wheel-legged robot is simplified into an n-order inverted pendulum model.

[0110] Taking the forward direction of the wheel-legged robot as the positive x-axis direction, the rightward movement direction as the positive y-axis direction, and the upward direction perpendicular to the contact surface as the positive z-axis direction, a world coordinate system is established.

[0111] As Figure 11 shown, in the two-dimensional model, the direction of rotating the mobile wheel to the left side of the contact surface is taken as the positive direction, the traveling distance is x, and the angle by which the wheel rotates relative to the world coordinate system is defined as The counterclockwise direction is taken as the positive direction of the wheel rotation angle. The angle by which the first link 1110 obtained by equivalent transformation of at least two leg mechanisms rotates relative to the world coordinate system is defined as α, and the counterclockwise direction is positive. The angle by which the second link (the other link except the first link among the n links) 1130 corresponding to the torso mechanism rotates relative to the world coordinate system is defined as β. The counterclockwise direction is taken as the positive direction of the wheel rotation angle. Hereinafter, the first link is referred to as link B, and the second link is referred to as link P.

[0112] Define to be respectively the derivatives of α and β with respect to time; where, represents the rotation speed of the wheel (also referred to as the angle of the wheel), represents the angular velocity of the first link, represents the angular velocity of the second link; define to be respectively the second-order derivatives of α and β with respect to time; where, represents the angular acceleration of the wheel, represents the angular acceleration of the first link, represents the angular acceleration of the second link.

[0113] The angle by which the wheel rotates relative to the world coordinate system is driven by the joint motor on the first rotating joint (equivalent to Figure 11 1120 in

[0114] The angle by which the second link rotates relative to the world coordinate system is driven by the joint motor of the second rotating joint (equivalent to Figure 11 1140 in

[0115] The masses of the wheel, link B (equivalent to at least two non - coincident leg mechanisms), and link P (equivalent to the torso mechanism) are respectively denoted as m W , m B , m P ; the moments of inertia of the wheel, link B, and link P are respectively denoted as: J W , J B , J P . The radius of the wheel is denoted by r, and the length of link B is denoted by L B . The length of the line connecting the intersection point of link B and the wheel to the geometric center of link B is denoted by l B . The length of the line connecting the intersection point of link B and the wheel to the geometric center of link P is denoted by l P .

[0116] (1) On the basis of defining the above physical quantities, respectively derive the expressions for the total kinetic energy T W of the wheel, the total kinetic energy T B of link B, and the total kinetic energy T P of link P, and obtain the total kinetic energy T of the wheel - leg robot system; among them, the total kinetic energy T W of the above - mentioned wheel, the total kinetic energy T B of link B, and the total kinetic energy T P of link P all include translational kinetic energy and rotational kinetic energy in the calculation of kinetic energy.

[0117]

[0118]

[0119]

[0120] T = T W + T B + T P

[0121] (2) Calculate the partial derivatives of the total kinetic energy T of the system with respect to each degree of freedom (α, β, ) in the generalized coordinates, and the derivatives of each degree of freedom with respect to time respectively. The specific process is as follows:

[0122] The partial derivative of the total kinetic energy T of the system with respect to the angular velocity of the wheel is expressed as:

[0123]

[0124] The partial derivative with respect to time is expressed as:

[0125]

[0126] The partial derivative of the total kinetic energy T of the system with respect to the angular velocity of the first link is expressed as:

[0127]

[0128] The derivative of the partial derivative with respect to time is expressed as:

[0129]

[0130]

[0131] The partial derivative of the total kinetic energy T of the system with respect to the angular velocity of the second link is expressed as:

[0132]

[0133] The derivative of the partial derivative with respect to time is expressed as:

[0134]

[0135] The partial derivative of the total kinetic energy T of the system with respect to the deflection angle of the wheel is expressed as:

[0136]

[0137] The partial derivative of the total kinetic energy T of the system with respect to the deflection angle α of the first link is expressed as:

[0138]

[0139] The partial derivative of the total kinetic energy T of the system with respect to the deflection angle β of the second link is expressed as:

[0140]

[0141] (3) Calculate the total potential energy U of the system:

[0142] U = m B gl B cosα + m B gl B cosα + m P g(L B cosα + l P cosβ)

[0143] It should be noted that in the above formula, the plane where the moving wheel is located is taken as the zero potential energy surface, that is, the potential energy of the moving wheel is considered to be 0. Therefore, the potential energy of the wheel does not appear in the formula for the total potential energy U of the above system. Of course, other potential energy surfaces can also be selected, which will not affect the implementation of the balance control method. This application does not limit the potential energy surface used in the process of calculating the total potential energy of the system.

[0144] (4) Calculate the results of taking the partial derivatives of the total potential energy U of the system with respect to each degree of freedom in the generalized coordinates:

[0145] The partial derivative of the total potential energy U of the system with respect to the deflection angle of the moving wheel is expressed as:

[0146]

[0147] The partial derivative of the total potential energy U of the system with respect to the deflection angle α of the first link is expressed as:

[0148]

[0149] The partial derivative of the total potential energy U of the system with respect to the deflection angle β of the second link is expressed as:

[0150]

[0151] (5) Using the above various formulas, based on the Euler - Lagrange equation, the dynamic equation of the wheel - legged robot under the second - order inverted pendulum model can be derived:

[0152]

[0153]

[0154]

[0155] m αα =(m B l B 2 +J B +m P L B 2 +J P )

[0156] m αβ =m P L B l P cosαcosβ+m P L B l P sinαsinβ+JP

[0157] m ββ = (m P l P 2 + J P )

[0158]

[0159]

[0160]

[0161]

[0162] g α = -(m B gl B + m P gL B )sinα

[0163] g β = -m P gl P sinβ

[0164] The dynamic equation can be written in polynomial form:

[0165]

[0166]

[0167]

[0168] Write the dynamic equation in polynomial form as a dynamic equation in matrix form:

[0169]

[0170] where M(α,β) is a 3×3 inertia matrix; specifically including

[0171] Each element in M(α,β) is each element in the inertia matrix, used to characterize the mass and moment of inertia of each joint rigid body forming the wheel-legged robot when the deflection angle of the first link is α and the deflection angle of the second link is β, as well as the equivalent inertia physical quantities of each link under mutual influence. is a 3×1 deviation force matrix, which can also be called a deviation force vector, specifically including: Used to characterize the Coriolis force and centripetal force received by each link of the wheel-leg robot; G(α,β) represents a 3*1 gravity matrix, which can also be called a gravity vector, specifically including [0g α g β T . τ1 represents the driving torque of the first rotating joint, and τ2 represents the driving torque of the second rotating joint.

[0172] After deriving the dynamic equation in matrix form through the above process, the dynamic equation in this matrix form can be directly used in the subsequent balance control process without repeating the above derivation process in the balance control process.

[0173] Next, the n-order inverted pendulum model will be introduced and explained.

[0174] The world coordinate system adopted in this example is the same as the definition of the world coordinate system in the corresponding part of the Figure 11 embodiment content. Of course, other methods can also be used to define the world coordinate system, and this application does not limit it here.

[0175] As Figure 12 shown, the n-order inverted pendulum consists of n links, n rotating joints and a moving wheel; among them, the moving wheel is connected to the first link among the n links, and the n links are connected in series. n is a positive integer greater than or equal to 2. Exemplarily, the moving wheel in the n-order inverted pendulum corresponds to the moving wheel of the wheel-leg robot. In the case where the wheel-leg robot has multiple moving wheels, the multiple moving wheels can be equivalent to the wheel in the n-order inverted pendulum model, and the rotation angle of the wheel is expressed as

[0176] Two adjacent links among the n links of the n-order inverted pendulum model are connected by a rotating joint, and the deflection angles of the n links are respectively: q1, q2,..., q n ; where, q1 is the deflection angle of the first link, q2 is the deflection angle of the second link, and so on, q n is the deflection angle of the nth link. Taking the first link as an example to illustrate the deflection angle of the link: As Figure 12 shown, in this derivation process, the deflection angle of the first link refers to the deflection angle of the first link relative to the z-axis in the world coordinate system. Of course, other methods can also be used to define the deflection angle of the first link. In this case, the derivation process of the dynamic equation of the n-order inverted pendulum model is similar to the process of this embodiment and will not be elaborated.

[0177] Exemplarily, when the wheel-leg robot is in a standing posture, the distance l1 between the first link and the contact surface < the distance l2 between the second link and the contact surface <... < the distance l between the nth link and the contact surface n ​The leg mechanism is connected to the corresponding moving wheel through a real rotating joint. Optionally, a link refers to a simplified model of each mechanism included in the wheel-legged robot. The wheel-legged robot can have multiple components, each component can be called an "institution", and each institution can be simplified as a link. Among them, the first link is a link obtained by equivalent of at least two non-coincident leg structures.

[0178] In some cases, the wheel-legged robot is in a posture where multiple moving wheels are in contact with the contact surface, and the multiple moving wheels are connected to their respective leg mechanisms; for any one of the multiple moving wheels, the rotating joint connecting the moving wheel to its corresponding leg mechanism is called a real rotating joint, and at least two real rotating joints are equivalently obtained as the first rotating joint.

[0179] After understanding the n-order inverted pendulum model, the dynamic equation of the n-order inverted pendulum model is constructed in a way similar to the corresponding dynamic equation of the second-order inverted pendulum model.

[0180] Specifically, determine the total kinetic energy (the total kinetic energy includes: translational kinetic energy and rotational kinetic energy) and potential energy corresponding to the n links and wheels respectively, add the kinetic energies of the n links and wheels to obtain the total system kinetic energy of the wheel-legged robot, and add the potential energies of the n links and wheels to obtain the total system potential energy of the wheel-legged robot.

[0181] For any one of the multiple degrees of freedom in the generalized coordinate system (including the deflection angles of each link, the angular velocities of each link, the rotation angles of the wheels, and the angular velocities of the wheels), determine the partial derivative of the total system kinetic energy with respect to this degree of freedom, and determine the derivative of this partial derivative with respect to time.

[0182] For any one of the multiple degrees of freedom in the generalized coordinate system, determine the partial derivative of the total system kinetic energy with respect to this degree of freedom. According to the partial derivatives of the system kinetic energy with respect to each degree of freedom, the derivatives of each partial derivative with respect to time, and the derivatives of each partial derivative with respect to time, the system dynamic equation of the n-order inverted pendulum is determined by the Euler-Lagrange equation:

[0183]

[0184] Among them, refers to the inertia matrix, including the masses and moments of inertia of the n rotating joints (regarding the rotating joints as joint rigid bodies) of the wheel-legged robot involved in the n-order inverted pendulum model, q is a vector, and the transposed vector q of q T =[q1 q2…q n , refers to the angular velocity of the wheel, refers to the angular acceleration of the wheel, represents the angular velocity of n linkages, is a vector, and the transposed vector of represents the angular acceleration of n linkages, is a vector, and the transposed matrix of refers to the deviation force matrix, which is used to characterize the deviation forces received by each linkage when the wheel-legged robot is at an angle of the wheel as the deflection angles of n linkages are q1, q2,..., q n in the posture, including centripetal force and Coriolis force. is the gravity matrix, which is used to characterize the gravity received by each of the n linkages when the wheel-legged robot is at an angle of the wheel as the deflection angles of n linkages are q1, q2,..., q n in the posture.

[0185] Since the plane where the moving wheel is located is determined as the 0 potential energy surface, the first item in the G matrix is 0, indicating that the gravity corresponding to the moving wheel on this 0 potential energy surface is zero. Of course, other 0 potential energy surfaces can also be selected, and this application does not limit this here. I n represents the n×n identity matrix, τ T = [τ1 τ2... τ n , representing the driving torques corresponding to n rotating joints.

[0186] Next, the balance control method after abstracting the wheel-legged robot into an n-order inverted pendulum will be introduced. This method is mainly realized by the cooperation of other modules such as the robust controller and the whole-body dynamics controller in the control system. For specific content, please refer to the following embodiments.

[0187] Please refer to Figure 13 , which shows the flowchart of the balance control method of the wheel-legged robot provided by an embodiment of this application. The execution subject of each step of this method can be a computer device. The wheel-legged robot is simplified into an n-order inverted pendulum model, and the n-order inverted pendulum model includes: a wheel, n linkages, and n rotating joints. The wheel and the first linkage among the n linkages are connected through the first rotating joint among the n rotating joints. The n linkages are serially connected through n - 1 rotating joints except the first rotating joint. The first linkage is the equivalent linkage corresponding to at least two leg mechanisms of the wheel-legged robot, and the wheel is the equivalent moving wheel corresponding to the moving wheels respectively connected by at least two leg mechanisms. n is a positive integer greater than or equal to 2. This method may include at least one of the following steps (1310 - 1350):

[0188] Step 1310: Obtain the actual state quantities of the wheel-legged robot at the first moment. The actual state quantities are used to characterize the motion states of n - 1 linkages, at least two leg mechanisms, and at least two mobile wheels. The n - 1 linkages are the other linkages among the n linkages except the first linkage.

[0189] In some embodiments, the mobile wheels are used to contact the contact surface. The rotating joint refers to the joint driven by a joint motor. The n linkages refer to the linkages connected to at least one of the n rotating joints. Optionally, the n rotating joints serially connect the n linkages into a linear shape.

[0190] In some embodiments, for any one of the at least two mobile wheels, the leg mechanism is connected to the mobile wheel through a real rotating joint, and different mobile wheels correspond to different real rotating joints. Optionally, the number of mobile wheels included in the wheel-legged robot is equal to the number of real rotating joints. Optionally, the number of mobile wheels included in the wheel-legged robot is equal to the number of leg mechanisms.

[0191] Optionally, the at least two mobile wheels do not overlap in the yoz plane of the world coordinate system, and the at least two leg mechanisms do not overlap on the yoz plane of the world coordinate system. For the specific introduction of this content, please refer to the above embodiments and will not be elaborated here. By equivalently regarding the at least two mobile wheels as wheels, regarding the at least two leg mechanisms as the first linkage, and combining the wheels, the first linkage with the n - 1 linkages in the wheel-legged robot, the wheel-legged robot can be abstracted into the nth-order inverted pendulum model introduced above. The balance control method provided by the embodiments of the present application is designed based on the nth-order inverted pendulum model.

[0192] Exemplarily, the wheel-legged robot includes multiple components. Each component (excluding the active joint) can be called an institution, and the institution can be simplified as a linkage. The n rotating joints can be rotary joints. In the ideal state, the linkages do not undergo bending deformation.

[0193] In some embodiments, any one of the n linkages is respectively an independent linkage (for example, the leg mechanism in the wheel-legged robot is used as one linkage, and the torso mechanism is used as one linkage).

[0194] Exemplarily, at least one of the n linkages includes a combined linkage composed of m independent linkages connected by joints, where m is a positive integer greater than 1. In this case, the joints used to connect the m independent linkages do not rotate or move linearly during the balance control process. For example, these joints are locked during the balance control, so that the linkage combination composed of the m independent linkages can be regarded as one of the n linkages.

[0195] In some embodiments, the first link refers to the link that is connected to the wheel through a first rotating joint in an n-degree inverted pendulum model. Optionally, in the direction perpendicular to the contact surface (i.e., the z-axis direction in the world coordinate system), among the n links, the distance between the first link and the wheel is the smallest. As can be determined from the above content, the first link is equivalently obtained from at least two non-coincident leg mechanisms.

[0196] Optionally, if the leg mechanism of the wheel-legged robot is a straight leg, the first link is obtained from at least two non-coincident leg mechanisms of the wheel-legged robot; if the leg mechanism of the wheel-legged robot is a jointed leg, that is, the leg mechanism includes two sub-mechanisms connected by a knee joint, and the knee joint is used to control the joint angle between the two sub-structures, the first link is equivalently obtained from the sub-mechanism directly connected to the first joint in the leg mechanism.

[0197] In the present application, n is a positive integer greater than 1. For example, n is equal to 2, 3, 4, 5,.... The maximum value of n is related to the structure of the wheel-legged robot, and the present application does not limit it here.

[0198] Exemplarily, when n is equal to 2, the n links respectively correspond to the leg mechanism and the torso mechanism of the wheel-legged robot. Exemplarily, when n is equal to 3, the n links respectively correspond to the leg mechanism (the leg mechanism is a straight leg), the torso mechanism, and the head mechanism of the wheel-legged robot. Exemplarily, when n is equal to 3, the n links respectively correspond to the leg mechanism (the leg mechanism is a straight leg), the torso mechanism, and the robotic arm mechanism of the wheel-legged robot. Exemplarily, when n is equal to 4, the n links respectively correspond to the leg mechanism (the leg mechanism is a straight leg), the torso mechanism, the first robotic arm link connected to the torso mechanism, and the second robotic arm link connected to the first robotic arm, or the robotic hand. Exemplarily, when n is equal to 4, the n links respectively correspond to the first sub-mechanism of the leg mechanism (the leg mechanism is a straight leg), the second sub-mechanism connected to the first sub-mechanism through the knee joint, the torso mechanism, and the first robotic arm link connected to the torso mechanism. Among them, the first link among the n links corresponding to the leg mechanism means that the first link is equivalently obtained from multiple non-coincident leg mechanisms.

[0199] Optionally, n rotating joints are used to serially connect n linkages. Exemplarily, any one of the n rotating joints respectively corresponds to the same type of real rotating joint. For example, in the case where a wheel-legged robot includes multiple moving wheels, there are multiple real rotating joints respectively used to connect each moving wheel with its corresponding leg mechanism, and these multiple real rotating joints together correspond to the first rotating joint among the n rotating joints. That is to say, the first rotating joint in the nth-order inverted pendulum model is equivalently obtained by at least two real rotating joints, and the at least two real rotating joints refer to the rotating joints respectively connected to the at least two moving wheels that do not overlap in the forward direction.

[0200] It should be noted that the value of n is related to the configuration of the wheel-legged robot, the computing power of the computer, power consumption and other actual requirements, and is not limited herein in this application. The larger the number of n, the more linkages with adjustable postures there are during the balance control process, making the posture of the wheel-legged robot more diverse during the balance adjustment process, which helps to improve the balance ability of the wheel-legged robot to cope with external disturbances.

[0201] In some embodiments, the first moment is any moment during the movement process of the wheel-legged robot.

[0202] Optionally, at the first moment, the posture of the wheel-legged robot is such that at least two moving wheels in contact with the contact surface (such as moving wheel A and moving wheel B) do not overlap in the forward direction of the wheel-legged robot (the x-axis direction in the world coordinate system), and at least two leg mechanisms (such as leg mechanism 1 connected to moving wheel A and leg mechanism 2 connected to moving wheel B) do not overlap in the forward direction of the wheel-legged robot. Exemplarily, the wheel-legged robot has 4 moving wheels, and at the first moment, the wheel-legged robot is in a four-wheel balance mode or a two-wheel - four-wheel switching mode. Exemplarily, leg mechanism 1 belongs to the outer leg mechanism group, and leg mechanism 2 belongs to the inner leg mechanism group.

[0203] In some embodiments, the actual state quantity is used to describe the motion state of the wheel-legged robot at the first moment. According to the actual state quantity at the first moment, the posture and motion state of the wheel-legged robot at the first moment can be determined. Optionally, the actual state quantity at the first moment is observed by the sensors of the wheel-legged robot.

[0204] Optionally, the actual state quantity at the first moment includes at least one of the following: the deflection angles of at least two leg mechanisms …, the deflection angles q2, …, q of (n - 1) linkages n , the angular velocities respectively corresponding to at least two moving wheels …, the angular velocities of at least two leg mechanisms … and the angular velocities of (n - 1) linkages

[0205] Exemplarily, each physical quantity included in the actual state quantity is observed in the world coordinate system; among them, the deflection angle of the leg mechanism refers to the deflection angle of the leg mechanism relative to the z-axis in the world coordinate system, and the deflection angle q i (i ∈ [2, n]) of the i-th link among the n - 1 links refers to: the deflection angle of the i-th link relative to the z-axis in the world coordinate system; the angular velocity of the moving wheel refers to: the rotational speed of the moving wheel in the clockwise direction of the x-axis in the world coordinate system; the angular velocity of the leg mechanism refers to the change speed of the deflection angle of the leg mechanism relative to the z-axis in the world coordinate system; the angular velocity of the i-th link is used to characterize the angular velocity of the i-th link, that is, the change speed of the deflection angle of the i-th link.

[0206] It should be noted that each physical quantity in the state quantity can also be represented by the relative positions between the various links of the wheel-legged robot. For example, the deflection angle q j ′(i ∈ [2, n]) of the j-th link refers to: the deflection angle of the j-th link relative to the j - 1-th link; among them, the j - 1-th link and the j-th link are connected by a rotating joint. Optionally, the distance between the j-th link and the contact surface is greater than the distance between the j - 1-th link and the contact surface. It should be noted that the observation coordinate systems corresponding to the respective physical quantities in the actual state quantity can be determined according to actual needs, and this application does not limit it here.

[0207] In this application, the physical quantities in each formula are observed based on the world coordinate system. Of course, the physical quantities determined using other observation coordinate systems can also implement this balance control method, and the relevant formulas can be obtained by making equivalent substitutions based on the formulas provided in this application, which will not be mentioned one by one in the text.

[0208] Optionally, obtaining the actual state quantity of the wheel-legged robot at the first moment includes: determining the deflection angles of at least two leg mechanisms through the IMU sensor and the motor encoder …, and the deflection angles q2,..., q of the n - 1 links n ; determining the angular velocity of the moving wheel through the motor encoder the angular velocities of at least two leg mechanisms … and the angular velocities of the n links

[0209] Exemplarily, the clock cycles of the various IMU sensors and motor encoders in the wheel-legged robot are the same or in a multiple relationship, so that each physical quantity included in the actual state quantity is a physical quantity at the first moment. For the specific content of the IMU encoder and the motor encoder, please refer to the above introduction and will not be elaborated here.

[0210] In some embodiments, the robust controller uses the actual state quantity at the first moment as input information and performs a balancing control process based on the actual state quantity at the first moment.

[0211] Step 1320: Process the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment. The equivalent state quantity is used to characterize the motion states of the n linkages and the wheels.

[0212] In some embodiments, the equivalent state quantity refers to the state quantity required for the balancing control process, and at least one physical quantity included in the equivalent state quantity is related to the n-order inverted pendulum model.

[0213] Optionally, the equivalent state quantity at the first moment includes at least one of the following: the deflection angles q1, q2,..., q of the n linkages n , the angular velocity of the wheel the angular velocities of the n linkages

[0214] Exemplarily, the equivalent state quantity consists of: the deflection angles q1, q2,..., q of the n linkages n , the angular velocity of the wheel the angular velocities of the n linkages The equivalent state quantity can be represented by the symbol ξ, and the state quantity ξ can be expressed as:

[0215]

[0216] where, q T represents the transposed vector of the vector q, q T = [q1 q2...q n , represents the transposed vector of the vector ,

[0217] Optionally, the computer device performs equivalence on the physical quantities related to at least two leg mechanisms to obtain the physical quantities related to the first linkage, and performs equivalence on the state quantities related to at least two mobile wheels to obtain the physical quantities related to the wheels in the equivalent state quantity. For the specific content of this process, please refer to the following embodiments and will not be elaborated here.

[0218] It should be noted that during the balancing control process, the state parameters in the equivalent state quantity are used for calculation, and in the following text, except for the "actual state quantity", the "state quantity" can represent the "equivalent state quantity".

[0219] Step 1330: Establish a sliding mode surface based on the equivalent state quantity at the first moment, and the equivalent state quantity gradually approaches 0 on the sliding mode surface.

[0220] In some embodiments, the sliding mode surface can be understood as a hypothetical vector plane in sliding mode control. The state variables of the wheel-legged robot gradually tend to 0 on the sliding mode surface. That is to say, the state of the wheel-legged robot can gradually tend to equilibrium on the sliding mode surface. The sliding mode surface can be represented by the symbol s. Optionally, the sliding mode surface is a rational number, and the value of the sliding mode surface can be greater than 0, equal to 0, or less than 0.

[0221] Optionally, the sliding mode surface is a linear sliding mode surface that has a linear relationship with the state variables, or the sliding mode surface belongs to a sliding mode surface with a high-order mapping relationship between the state variables. Considering the purposes of reducing the computational pressure of the robust controller and the energy consumption of the wheel-legged robot during the actual application process, in the embodiments of this article, mainly taking the creation of a linear sliding mode surface as an example, the method for determining the sliding mode surface according to the state variables is introduced and described.

[0222] In some embodiments, the number of sliding mode surfaces that the robust controller needs to establish is related to the number of rotational torques to be determined. Optionally, the number of sliding mode surfaces that the robust controller needs to establish is equal to the number of rotational torques to be determined. In this application, the wheel-legged robot is abstracted into an n-order inverted pendulum model, which involves a total of n rotational joints, and each of the n rotational joints has an independent rotational torque. Therefore, the rotational torques at the second moment include: the rotational torques of the n rotational joints, and n sliding mode surfaces need to be established; among them, any two of the n sliding mode surfaces are different sliding mode surfaces. For the specific steps of establishing the sliding mode surface, please refer to the embodiments below.

[0223] Step 1340, according to the sliding mode surface, the equivalent state variables at the first moment, and the dynamic equation of the wheel-legged robot, determine the force and torque commands for the whole body joints of the wheel-legged robot. The whole body joints include n rotational joints, and the dynamic equation is established based on the n-order inverted pendulum model.

[0224] Optionally, the whole body joints include the active joints in the wheel-legged robot. Exemplarily, the whole body joints include n rotational joints and other active joints in the wheel-legged robot except for the n rotational joints.

[0225] In some embodiments, the computer device determines the force and torque commands for the whole body joints of the wheel-legged robot according to the sliding mode surface, the equivalent state variables at the first moment, and the dynamic equation of the wheel-legged robot, including: determining the rotational torques of the n rotational joints according to the sliding mode surface, the equivalent state variables at the first moment, and the dynamic equation of the wheel-legged robot; calculating the task acceleration of the wheel-legged robot through the rotational torques of the n rotational joints; and calculating the force and torque commands for the whole body joints of the wheel-legged robot by the whole body dynamics controller in the control system of the wheel-legged robot according to the task acceleration of the wheel-legged robot.

[0226] Optionally, this step is completed by multiple controllers in the wheel-legged robot. Among them, the robust controller participates in the calculation process of the driving torques of n rotating joints, and the whole-body dynamics controller calculates the force and torque commands of the whole-body joints of the wheel-legged robot according to the task acceleration. In some cases, direct interaction between the robust controller and the whole-body dynamics controller is not possible, so the observation module also needs to participate in step 1340.

[0227] Exemplarily, the step of calculating the task acceleration of the wheel-legged robot through the driving torques of n rotating joints is performed by the observation module in the control system of the wheel-legged robot. A connection is established between the observation module and the robust controller, and a connection is established between the observation module and the whole-body dynamics controller. The observation module obtains the driving torques of n rotating joints from the robust controller, calculates the task acceleration according to the driving torques of the rotating joints, and transmits the task acceleration to the whole-body dynamics controller; the whole-body dynamics controller determines the forces and torques corresponding to the whole-body joint motors respectively according to the task acceleration and executes them. For the specific process of this step, please refer to the embodiments below.

[0228] By associating the control results (the above two driving torques) of the robust controller with the whole-body dynamics controller, the whole-body dynamics controller can receive information related to balance control, which helps the whole-body dynamics controller to perform reasonable optimization according to the various input information it receives, generate optimized joint commands (i.e., force and torque commands), and send these joint commands to the corresponding joints, so that more linkages in the wheel-legged robot can rotate during the balance control process, which helps to improve the balance control ability of the wheel-legged robot during the movement process.

[0229] For the specific introduction of this step, please refer to the embodiments below.

[0230] Step 1350, at the second moment, control the n - 1 rotating joints and the real rotating joints corresponding to the first rotating joint according to the force and torque commands of the whole-body joints.

[0231] In some embodiments, the second moment refers to any moment after the first moment. Optionally, the second moment refers to the moment after the force and torque commands of the whole-body joints are calculated.

[0232] In some embodiments, the n - 1 rotating joints can be understood as the other rotating joints included in the nth-order inverted pendulum model except for the first rotating joint. Since these rotating joints correspond one-to-one with the rotating joints in the wheel-legged robot, unlike the first rotating joint that corresponds to multiple real rotating joints, the force and torque commands of the n - 1 rotating joints can be directly used to control the corresponding rotating joints in the wheel-legged robot.

[0233] Optionally, this step is completed by a whole-body dynamics controller in the wheel-legged robot. After the whole-body dynamics controller determines the force and torque commands of the whole body joints, it determines the force and torque commands corresponding to the n rotating joints from the force and torque commands of the whole body joints, and sends these force and torque commands to the joint motors corresponding to the respective rotating joints, respectively, to control the joint motors to rotate according to the force and torque commands, thereby changing the posture of the wheel-legged robot.

[0234] In some embodiments, for the linear motors in at least two leg mechanisms, according to the force and torque commands of the whole body joints, the linear motors are controlled to move, and the linear motors in the leg mechanisms control the lengths of the leg mechanisms. For specific content, please refer to the following embodiments.

[0235] In summary, based on abstracting the wheel-legged robot into a multi-stage inverted pendulum model, during the balance control process, the deflection angles of multiple linkages in the wheel-legged robot can be adjusted to change the posture of the wheel-legged robot; compared with the related technologies that can only adjust the angle between the moving wheels and the leg mechanisms during the balance control process, this solution enables the postures of multiple linkages in the wheel-legged robot to be variable during the balance adjustment process, greatly enriching the robot postures, helping to quickly adjust the robot to the balanced state, and also helping to improve the ability of the robot to return to the balanced state under the action of different disturbing forces, and enhancing the robustness of the robot balance control process.

[0236] On the other hand, using the method provided in this application to determine the equivalent state quantity according to the actual state quantity enables the balance control in the multi-wheel motion mode to share a set of control parameters with the balance control in the two-wheel motion mode. After the wheel-legged robot switches the motion mode, it is not necessary to adjust the control parameters in the controller (such as a robust controller) used for balance control, which helps to improve the versatility of the controller.

[0237] The following introduces and illustrates the method for obtaining the equivalent state quantity at the first moment through several embodiments.

[0238] In some embodiments, step 1320 includes the following sub-steps (not shown in the accompanying drawings of the specification):

[0239] Sub-step 1321, superimpose the angular velocities of at least two moving wheels in the actual state quantity to obtain the angular velocity of the wheels.

[0240] In some embodiments, since the angular velocities of the non-coincident moving wheels in the forward direction are not equal, the angular velocity of the wheels is obtained by vectorially superimposing the angular velocities of at least two moving wheels. For example, at least two moving wheels include moving wheel 1 and moving wheel 2, the angular velocity of moving wheel 1 is v1, and the angular velocity of moving wheel 2 is v2, then the angular velocity of the wheels is equal to (v1 + v2) / 2.

[0241] Sub-step 1322: Determine the geometric relationship between at least two leg mechanisms according to the lengths and deflection angles of the at least two leg mechanisms.

[0242] In some embodiments, the geometric relationship between at least two leg mechanisms is used to characterize the positional relationship between the at least two leg mechanisms. Since one end of the at least two leg mechanisms is connected to the same joint, the other ends of the at least two leg mechanisms are respectively vectorized with their corresponding moving wheels. Optionally, the heights of one ends of the at least two leg mechanisms are the same, and the heights of the other ends are also the same. After determining the lengths of the at least two leg mechanisms, the included angle between the at least two leg mechanisms can be determined according to the deflection angles of the at least two leg mechanisms.

[0243] Sub-step 1323: Determine the deflection angle and angular velocity of the first link according to the geometric relationship, the deflection angles of the at least two leg mechanisms, and the angular velocities of the at least two leg mechanisms. Through the geometric joint, the positional relationship between the first link and the at least two leg mechanisms can be determined. According to the positional relationship, the relationship between the deflection angles of the two leg mechanisms and the deflection angle of the first link can be determined. Thus, the method for determining the deflection angle of the first link and the angular velocity of the first link is similar and will not be elaborated here.

[0244] Sub-step 1324: Use the deflection angles of n - 1 links in the actual state quantity as the deflection angles of n - 1 links in the equivalent state quantity.

[0245] Sub-step 1325: Use the angular velocities of n - 1 links in the actual state quantity as the angular velocities of n - 1 links in the equivalent state quantity.

[0246] By processing the actual state quantity to obtain the equivalent state quantity, the physical quantities corresponding to the virtual first link can be obtained, enabling the balance control method to be set based on the n - order inverted pendulum model.

[0247] The determination method of the sliding surface will be introduced and illustrated through several embodiments below.

[0248] The sliding surface includes n sliding surfaces, and the n sliding surfaces are used to constrain the driving torques of the n rotating joints. Optionally, there are no identical sliding surfaces among the n sliding surfaces, and the n sliding surfaces are used to jointly participate in the calculation process of the driving torque.

[0249] Step 1330 in the above embodiments further includes the following sub-steps (not shown in the accompanying drawings of the specification):

[0250] Sub-step 1333: For the i-th sliding surface among the n sliding surfaces, determine at least two sliding parameters, where i is a positive integer less than or equal to n.

[0251] In some embodiments, the sliding mode surface is related to at least one element in the state quantity, and the elements in the state quantity can also be referred to as state parameters, such as the equivalent state quantity including q1, q2, …, q n , all belong to state parameters.

[0252] For example, a certain sliding mode surface is related to the deflection angle of the first link and the acceleration of the first link in the equivalent state quantity. For another example, a certain sliding mode surface is related to the deflection angle of the i-th link and the acceleration of the i-th link. Optionally, the n sliding mode surfaces are respectively related to the first state parameter in the state quantity. For example, the first state parameter is the angular velocity of the moving wheel, that is, the n sliding mode surfaces are all related to the angular velocity of the moving wheel.

[0253] Optionally, the sliding mode parameter is a real number. The sliding mode parameter is used to characterize the proportional relationship between the state parameter in the state quantity and the sliding mode surface. Exemplarily, the sliding mode parameters between different sliding mode surfaces are not shared. That is to say, among the n sliding mode surfaces, there are at least two sliding mode surfaces, and the sliding mode parameters corresponding to the at least two sliding mode surfaces are not equal.

[0254] In some embodiments, the number of state parameters used to create the sliding mode surface is more than the number of sliding mode parameters. Optionally, for any one of the n sliding mode surfaces, the number of state parameters used in the creation process of this sliding mode surface is more than the number of sliding mode parameters used. By this method, it helps to ensure that a definite driving torque can be calculated according to the sliding mode surface and the dynamic model parameters.

[0255] For example, when establishing a certain sliding mode surface, 3 state parameters in the state quantity and 2 sliding mode parameters are required. For another example, when creating a certain sliding mode surface, 4 state parameters in the state quantity and 3 sliding mode parameters are required.

[0256] Since the number of sliding mode parameters used in the process of creating the sliding mode surface is less than the number of state parameters, the coefficient of at least one state parameter in the sliding mode surface is equal to 1, that is, there is no corresponding state parameter for these sliding mode parameters, and the remaining state parameters required to create a certain sliding mode surface correspond one by one to the sliding mode parameters.

[0257] In some embodiments, for the i-th sliding mode surface among the n sliding mode surfaces, the i-th sliding mode surface includes at least two sliding mode parameters. Optionally, the state parameters included in different sliding mode surfaces are not completely the same, and the number of state parameters required to create each sliding mode surface is equal. For example, the number of sliding mode parameters included in the n sliding mode surfaces is equal. Assume that 3 state parameters are used to create the i-th sliding mode surface, and 3 state parameters are also used to create the (i + k)-th sliding mode surface, where k is a positive integer and i + k is less than or equal to n.

[0258] In some embodiments, the number of sliding mode parameters included in the ith sliding mode surface is related to the number of state parameters used to establish the ith sliding mode surface. Optionally, the number of state parameters used to create the ith sliding mode surface is 1 more than the number of sliding mode parameters used to create the ith sliding mode surface. To ensure that a definite solution of the driving torques of n rotating joints can be calculated through the sliding mode surface and the dynamic model parameters, the ith sliding mode surface is related to at least 3 state parameters in the equivalent state quantity at the first moment. Optionally, at least 3 state parameters related to the ith sliding mode surface are not exactly the same as at least 3 state parameters related to the lth sliding mode surface, where l is a positive integer less than or equal to n.

[0259] To improve the reliability of the determined driving torque, the sliding mode parameters need to meet the system stability conditions. For the specific content of this part, please refer to the following embodiments.

[0260] Optionally, the number of state parameters used to create n sliding mode surfaces is equal. For example, any one of the n sliding mode surfaces includes 3 state parameters.

[0261] Taking the creation of the ith sliding mode surface as an example, the creation method of the sliding mode surface will be introduced and described below.

[0262] Generally speaking, the more state parameters in the equivalent state quantity at the first moment that are related to a certain sliding mode surface, the more reference information is used in the process of calculating the driving torques of n rotating joints; the mutual restriction between state parameters helps to improve the accuracy of the driving torques of n rotating joints determined according to n sliding mode surfaces and dynamic model parameters, and helps to improve the effect of balance adjustment.

[0263] Optionally, at least 3 state parameters and at least 2 sliding mode parameters are used to create the ith sliding mode surface.

[0264] Exemplarily, the state parameters used to create the $i$-th sliding surface include: the deflection angle of the $i$-th link, the angular velocity of the moving wheel, and the angular velocity of the $i$-th link; in this case, the two sliding mode parameters used to create the $i$-th sliding surface are respectively: the sliding mode parameter corresponding to the deflection angle of the $i$-th link, and the sliding mode parameter corresponding to the angular velocity of the moving wheel. Exemplarily, the $i$-th sliding surface is related to four state parameters in the state quantity. The $i$-th sliding surface is related to the deflection angle of the $i$-th link, the angular velocity of the moving wheel, the angular velocity of the $i$-th link, and the deflection angle of the $(i + m)\%n$-th link included in the state quantity, where $m$ is a positive integer that cannot be divided evenly by $n$, and “\%” represents taking the remainder of the division. In this case, the $i$-th sliding surface includes at least three sliding mode parameters, which are respectively: the sliding mode parameter corresponding to the deflection angle of the $i$-th link, the sliding mode parameter corresponding to the angular velocity of the moving wheel, and the sliding mode parameter corresponding to the deflection angle of the $(i + m)\%n$-th link. It should be noted that the number of state parameters and the number of sliding mode parameters related to the sliding surface are designed according to actual needs, and are not limited in this application.

[0265] In some embodiments, multiple sets of sliding surface creation schemes are designed in the robust controller. In different sliding surface creation schemes, the number of sliding mode parameters and the number of state parameters used to create the $i$-th sliding surface are not exactly the same. For example, in the first sliding surface creation scheme, creating the $i$-th sliding surface requires using 2 sliding mode parameters and 3 state parameters; in the second sliding surface creation scheme, creating the $i$-th sliding surface requires using 5 sliding mode parameters and 6 state parameters; that is, the number of sliding mode parameters used to create the sliding surface in the first sliding mode creation scheme is not equal to the number of sliding mode parameters required to create the sliding surface in the second sliding mode creation scheme; the number of state parameters used to create the sliding surface in the first sliding mode creation scheme is not equal to the number of state parameters required to create the sliding surface in the second sliding mode creation scheme.

[0266] Optionally, during the process of balance control, the robust controller selects a target creation scheme from multiple sets of sliding surface creation schemes according to the actual situation, and determines the number of sliding mode parameters required to create the $i$-th sliding surface according to the target creation scheme.

[0267] Exemplarily, when the computing performance of the robust controller is relatively high, the robust controller selects from multiple sets of sliding mode surface establishment schemes: the sliding mode surface creation scheme involving more sliding mode parameters as the target creation scheme. Exemplarily, the robust controller determines the target creation scheme according to the task currently executed by the wheel-legged robot; if the task currently executed by the wheel-legged robot has a relatively high requirement for balance and the robust controller has good computing power, then the robust controller selects, from multiple sets of sliding mode surface establishment schemes, the sliding mode surface creation scheme involving more sliding mode parameters as the target creation scheme. Exemplarily, when the computing performance of the robust controller is average or there is a power consumption requirement, the robust controller selects, from at least one set of sliding mode surface establishment schemes, the sliding mode surface creation scheme including fewer sliding mode parameters as the target creation scheme. Exemplarily, the robust controller receives a control instruction from the remote controller, and the control instruction is used to indicate the target creation scheme selected from multiple sliding mode surface creation schemes.

[0268] Sub-step 1336: Establish the i-th sliding mode surface according to the at least two sliding mode parameters and the equivalent state quantity at the first moment.

[0269] In some embodiments, the equivalent state quantity includes the deflection angles of n linkages, the angular velocity of the moving wheel, and the angular velocities of n linkages. Optionally, the robust controller creates the i-th sliding mode surface according to at least three state parameters in the equivalent state quantity at the first moment and at least two sliding mode parameters.

[0270] Optionally, step 1336: Establish the i-th sliding mode surface according to at least two sliding mode parameters and the equivalent state quantity at the first moment, including the following sub-steps:

[0271] Sub-step 1336-a: Process the deflection angle of the i-th linkage according to the first sliding mode parameter among the at least two sliding mode parameters to obtain the processing result of the i-th linkage.

[0272] Optionally, the first sliding mode parameter is the coefficient corresponding to the deflection angle of the i-th linkage, and the second sliding mode parameter is the coefficient corresponding to the angular velocity of the moving wheel linkage.

[0273] Optionally, the processing result of the i-th linkage refers to the result obtained by processing the deflection angle of the i-th linkage using the first sliding mode parameter during the process of constructing the i-th sliding mode surface. Exemplarily, the method of processing the deflection angle of the i-th linkage using the first sliding mode parameter includes but is not limited to: performing basic operations (such as addition, subtraction, multiplication, and division) on the first sliding mode parameter and the deflection angle of the i-th mechanism to obtain the processing result of the i-th linkage. For example, multiplying the first sliding mode parameter by the angular velocity of the i-th linkage to obtain the processing result of the first linkage.

[0274] Sub-step 1336-b: Process the angular velocity of the moving wheel according to the second sliding mode parameter among at least two sliding mode parameters to obtain the processing result of the moving wheel. Optionally, during the process of establishing the i-th sliding mode surface, the processing result of the moving wheel refers to the result obtained by processing the angular velocity of the moving wheel using the second sliding mode parameter. Exemplarily, the method of processing the angular velocity of the moving wheel using the second sliding mode parameter includes, but is not limited to: performing basic operations using the second sliding mode parameter and the angular velocity of the moving wheel. For example, multiplying the second sliding mode parameter by the angular velocity of the moving wheel to obtain the processing result of the moving wheel.

[0275] It should be noted that the second sliding mode parameters corresponding to different sliding mode surfaces are different, that is, for the creation processes of different sliding mode surfaces, processing the angular velocity of the moving wheel using the second sliding mode parameter results in different processing results of the moving wheel.

[0276] Sub-step 1336-c: Establish the i-th sliding mode surface according to the processing result of the i-th link, the processing result of the moving wheel, and the angular velocity of the i-th link.

[0277] In some embodiments, the i-th sliding mode surface is proportional to the processing result of the i-th link, the i-th sliding mode surface is proportional to the processing result of the moving wheel, and the first sliding mode surface is proportional to the angular velocity of the i-th link. Exemplarily, the robust controller adds the processing result of the i-th link, the processing result of the moving wheel, and the angular velocity of the i-th link to obtain the i-th sliding mode surface.

[0278] Optionally, the robust controller establishes the i-th sliding mode surface according to the processing result of the i-th link, the processing result of the moving wheel, the angular velocity of the i-th link, and a sliding mode constant, and the sliding mode constant can be a preset value. Exemplarily, the robust controller adds the processing result of the i-th link, the processing result of the moving wheel, the angular velocity of the i-th link, and the sliding mode constant to obtain the i-th sliding mode surface.

[0279] The robust controller determines n sliding mode surfaces respectively through the above method of creating the i-th sliding mode surface.

[0280] The n sliding mode surfaces can be represented by the following formula:

[0281]

[0282] where s represents a sliding mode surface matrix including n sliding mode surfaces; the first sliding mode parameters respectively corresponding to the deflection angles of n links, the second sliding mode parameters respectively corresponding to the angular velocity of the moving wheel in n sliding mode surfaces, and the explanations of other parameters can be referred to the above introduction and will not be elaborated.

[0283] In this way, n sliding mode surfaces are established. While ensuring that the driving torques of the n rotating joints can be calculated based on the sliding mode surfaces and the dynamic model parameters in the subsequent process, the number of sliding mode parameters and state parameters used in the process of creating the screen is controlled, which helps to control the computational cost of calculating the driving torques of the n rotating joints, helps to speed up the determination of the driving torques, reduce power consumption, and achieve the balance control of the robot.

[0284] The following introduces and illustrates the method for determining the forces and torque commands of the whole body joints through several embodiments. The execution subject of each step in this process can be a computer device.

[0285] Step 1340 in the above embodiments may include sub-step 1343 (not shown in the accompanying drawings of the specification):

[0286] First, the method for determining the driving torques of the n rotating joints is introduced and illustrated.

[0287] In sub-step 1343, the driving torques at the second moment are calculated according to the dynamic equation and the sliding mode surface. The driving torques at the second moment include: the driving torques of the n rotating joints.

[0288] In some embodiments, calculating the driving torques at the second moment according to the dynamic equation and the sliding mode surface includes: determining the dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment. The dynamic model parameters are used to define the mapping relationship between the angular acceleration at the first moment and the driving torques at the second moment; the angular acceleration at the first moment includes the angular accelerations of the n linkages; calculating the driving torques at the second moment according to the dynamic parameters and the sliding mode surface.

[0289] The following introduces and illustrates the method for determining the dynamic model parameters through several embodiments.

[0290] In some embodiments, the angular acceleration at the first moment refers to the rotational accelerations of the n linkages after abstracting the wheel-legged robot into an n-order inverted pendulum model (which can also be understood as the angular accelerations of the joint motors corresponding to the n rotating joints). The angular acceleration at the first moment can be represented by represented.

[0291] As can be seen from the above content, after abstracting the wheel-legged robot into an n-order inverted pendulum model, the dynamic equation in matrix form can be obtained:

[0292]

[0293] In the embodiments of this method, a robust controller in the control system of the wheel-legged robot is designed based on this equation, so that the robust controller can implement the balance control method provided in the embodiments of this application.

[0294] Based on the physical relationships among acceleration, velocity, and position, it can be known that the angular velocities of n linkages at the next moment after the first moment and the posture of the wheel-legged robot at subsequent moments can be predicted through the acceleration at the first moment. Moreover, the rotational torque of the joints can change the velocity and posture of the wheel-legged robot; in the design of the robust controller in this solution, the focus is on the dynamic equation in matrix form to establish the mapping relationship between the acceleration of the wheel-legged robot and the rotational torque of the joints.

[0295] Exemplarily, a partial feedback linearization process is performed on the dynamic equation in matrix form, such that the matrix related to the acceleration of the wheel-legged robot is on one side of the dynamic equation, and the matrix formula related to the rotational torque of the rotating joints is on the other side, to determine the mapping relationship between the acceleration at the first moment and the rotational torque. The mapping relationship between the acceleration at the first moment and the rotational torque of the rotating joints is represented by dynamic parameters. This process is completed during the design process of the robust controller, and the relevant formulas do not need to be repeatedly derived during actual balance control.

[0296] In some embodiments, the dynamic model parameters are used to characterize the linear mapping relationship between the acceleration and the rotational torque at the first moment. That is to say, through the dynamic model parameters, the following is satisfied: the acceleration and the rotational torque at the first moment satisfy an equal relationship in the formula obtained by converting based on the dynamic formula. Since there is more than one acceleration and rotational torque at the first moment, the dynamic model parameters can be represented in matrix form.

[0297] Exemplarily, the dynamic model parameters include: a proportional parameter matrix g[] and an offset parameter matrix f[]; among them, the proportional parameter matrix g[] is used to characterize the proportional relationship between the acceleration and the rotational torque at the first moment, and the offset parameter matrix f[] is used to characterize the offset between the acceleration and the rotational torque at the first moment. For the calculation methods of the above two dynamic model parameter matrices, please refer to the following embodiments.

[0298] Optionally, during the design process of the robust controller, the representation form of the dynamic model parameters is pre-determined. After obtaining the state quantity at the first moment, the robust controller substitutes the state quantity at the first moment into the representation form of the dynamic model parameters, and the numerical values of each element included in the dynamic model parameters can be determined.

[0299] In some embodiments, determining the dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment includes the following steps:

[0300] Step 10 (not shown in the figure), substitute the equivalent state quantity at the first moment into the dynamic equation to determine the inertia matrix, the bias force matrix, and the gravity matrix at the first moment. The inertia matrix is used to characterize the mass and moment of inertia of the n rotating joints at the first moment. The bias force matrix is used to characterize the bias force of the wheel-legged robot at the first moment. The gravity matrix is used to characterize the gravity of the wheel-legged robot at the first moment.

[0301] In some embodiments, the inertia matrix is used to characterize the inertia quantities of the joint rigid bodies corresponding to the n rotating joints that make up the wheel-legged robot in the posture at the first moment. The inertia quantity includes at least one of the following: mass, moment of inertia. Optionally, the inertia matrix can be calculated according to the dynamic equation. In the case where the wheel-legged robot is abstracted into an nth-order inverted pendulum model, the inertia matrix is a matrix of size (n + 1) * (n + 1).

[0302] In some embodiments, the bias force matrix is used to characterize the Coriolis force and the centripetal force received by each link. Optionally, the bias force matrix includes the bias force caused by the deflection angle of the wheel and the bias force caused by the deflection angle of the n-link.

[0303] In some embodiments, the gravity matrix is used to characterize the gravity received by each link. Optionally, the gravity matrix includes the gravity received by the wheel and the gravity received by each of the n links. Optionally, the wheel is always in contact with the contact surface, and the height of the moving wheel remains unchanged during the balance control process. The plane where the center of mass of the wheel is located is used as the zero potential energy surface, and the gravity received by the wheel is 0 to reduce the computational overhead during the balance control process.

[0304] Among them, for the relevant content of the inertia matrix, the bias force matrix, and the gravity matrix, please refer to Figure 11 、 12 the corresponding content in the specification, which will not be elaborated here. The expressions of the respective elements in the above-mentioned inertia matrix, bias force matrix, and gravity matrix are also pre-derived from the dynamic formula; after determining the equivalent state quantity at the first moment, the robust controller calculates the specific values of the respective elements included in the inertia matrix, the bias force matrix, and the gravity matrix at the first moment according to the equivalent state quantity at the first moment and the representation forms of the respective elements in the inertia matrix, the bias force matrix, and the gravity matrix; and then obtains the inertia matrix, the bias force matrix, and the gravity matrix at the first moment.

[0305] Step 20 (not shown in the figure), determine the dynamic model parameters according to the inertia matrix, the bias force matrix, and the gravity matrix.

[0306] In some embodiments, the dynamic model parameters include: a proportional parameter matrix and an offset parameter matrix. The proportional parameter matrix is used to characterize the proportional relationship between the angular acceleration at the first moment and the driving torques of the n rotating joints, and the offset parameter matrix is used to characterize the offset relationship between the angular acceleration at the first moment and the driving torques of the n rotating joints. Optionally, the robust controller calculates the offset parameter matrix based on the inertia matrix, the bias force matrix, and the gravity matrix, and calculates the proportional parameter matrix based on the inertia matrix.

[0307] The rotational relationship between the acceleration of the wheel-legged robot and the driving torques of the n rotating joints can be determined through the dynamic model parameters. Subsequently, based on the dynamic model parameters and the sliding surface, the driving torques of the n rotating joints can be determined relatively quickly, which helps to reduce unnecessary conversions during the process of determining the driving torques of the rotating joints and relieve the computing pressure on the computer device.

[0308] In some embodiments, step 20 further includes the following sub-steps:

[0309] Sub-step 20-a (not shown in the figure), using the selection matrix to process the product between the inverse matrix of the inertia matrix and the bias force matrix, and the product between the inverse matrix of the inertia matrix and the gravity matrix respectively, to obtain the offset parameter matrix. The selection matrix is used to extract the driving torques of the n rotating joints from the dynamic equation.

[0310] Optionally, the elements in the selection matrix include three values: (0, 1, -1). The selection matrix is used to: make each driving torque in τ exist independently in the dynamic equation, that is, using the selection matrix to process the dynamic equation, so that the coefficients of the driving torques of each rotating joint in the dynamic equation have the same sign, and the dynamic equation does not include basic operations between the rotation matrices of any two rotating joints (such as τ1 - τ2, etc.).

[0311] Sub-step 20-b (not shown in the figure), using the selection matrix to process the inverse matrix of the inertia matrix, to obtain the proportional parameter matrix.

[0312] The derivation process of the dynamic model parameters is introduced and explained below.

[0313] After performing partial feedback linearization on the dynamic equation in matrix form, formula 1 is obtained:

[0314]

[0315] where M -1 (q) is the inverse matrix of the inertia matrix, M -1 (q)*M(q) = E, where E is the identity matrix. For the physical meanings of other parameters in formula 1, please refer to the above embodiments and will not be elaborated here.

[0316] Further, in order to simplify the execution logic in the balance control process and reduce the computational load of the robust controller, it is also necessary to adjust the above formula (1) during the design process of the robust controller. The formula (1) is processed using a selection matrix to obtain formula (2):

[0317]

[0318] Wherein, represents the offset parameter matrix, represents the proportional parameter matrix, S T is the selection matrix.

[0319] Optionally, formula (2) is derived after the wheel-legged robot is abstracted into an n-order inverted pendulum model. During the balance control process, after obtaining the state quantity at the first moment, the robust controller can calculate the proportional parameter matrix and the dynamic model parameter matrix according to formula (2) and the expressions of each element in the inertia matrix, the bias force matrix, and the gravity matrix obtained during the derivation process of the dynamic equation of the n-order inverted pendulum model.

[0320] In some embodiments, the above dynamic equation of the robot is derived based on the Euler-Lagrange equation after abstracting the wheel-legged robot into an n-order inverted pendulum model, and the moving wheels of the wheel-legged robot correspond to the wheels in the n-order inverted pendulum model. For the derivation process of the dynamic equation, please refer to the above embodiments and will not be elaborated here. Abstracting the wheel-legged robot into an n-order inverted pendulum model for balance control helps to adapt to the balance control requirements in different scenarios and improve the robustness of the balance control method.

[0321] Next, the process of the robust controller calculating the rotational torque at the second moment according to the dynamic parameters and the sliding surface will be introduced and explained.

[0322] After explaining the design method of the dynamic model parameters and the n sliding surfaces in the robust controller, the relevant content of the design of the robust controller for calculating the rotational torques of the n rotating joints according to the sliding surface and the dynamic model parameters will be introduced and explained:

[0323] After establishing the n sliding surfaces according to the state equivalent quantity, the robust controller determines the first-order derivative formulas of the n sliding surfaces with respect to time respectively, and uses the torque to represent the angular accelerations of the n connecting rods according to the dynamic equation (formula (2)), and after arrangement, the following formula (3) is obtained:

[0324]

[0325] Wherein, Denotes the first-order derivative of \(n\) sliding surfaces with respect to time respectively, is the \(f\) q in the offset parameter matrix \(f[]\) in Formula 2 above is the \(g\) q in the proportional parameter matrix \(g[]\) in Formula 2 above For other parameters, please refer to the above introduction and will not be elaborated here.

[0326] By transposing Formula 3, Formula 4 is obtained:

[0327]

[0328]

[0329]

[0330] where \(sgn()\) is the sign function, is a constant matrix, \(s\) T is the transpose matrix of the sliding mode matrix \(s\) including \(n\) sliding surfaces, and \(|s|\) represents the absolute value of \(n\) sliding surfaces, Denotes the first-order derivative of \(n\) sliding surfaces with respect to time. For other parameters, please refer to the above introduction and will not be elaborated here.

[0331] Optionally, Formulas 3 and 4 are calculated in real time by the robust controller during the balance control process.

[0332] Using the properties of the sliding surface, when the sliding surface is controlled to be equal to 0, the state parameters related to the sliding surface will gradually tend to 0 along the sliding surface, that is, the wheel-leg robot returns to the balanced state. The state quantities (state parameters in them) satisfy on the sliding surface:

[0333]

[0334] The angular velocities of \(n\) connecting rods can be inversely expressed by the above formula:

[0335]

[0336] The robust controller determines the first-order derivative of the angular velocities of \(n\) connecting rods with respect to time, and obtains Formula 5 that can represent the angular accelerations of \(n\) connecting rods:

[0337]

[0338] Since q is a vector including the deflection angles of n linkages, q is split: Let α represent q1 (the deflection angle of the first linkage), and let β represent That is, β includes the deflection angles of the linkages other than the first linkage among the n linkages. Then, the dynamic equation obtained based on the nth-order inverted pendulum model is written as:

[0339]

[0340]

[0341]

[0342] Among them, in this formula represents the angular acceleration of the first linkage; represents the angular accelerations respectively corresponding to the linkages other than the first linkage among the n linkages; represents the inertia quantity related to the moving wheel in the inertia matrix M; represents the inertia quantity related to the first linkage among refers to the inertia quantity unrelated to the first linkage among αα represents m in the inertia matrix M qq the inertia quantity related to the first linkage among ββ represents m in the inertia matrix M qq the inertia quantity unrelated to the first linkage among α represents the biasing force received by the first linkage; c β represents the eccentric forces respectively received by the linkages other than the first linkage among the n linkages; g α represents the gravity received by the first mechanism; g β represents the gravity respectively received by the linkages other than the first linkage among the n linkages; τ1 represents the driving torque of the first rotating joint; τ2 represents the driving torques respectively corresponding to the rotating joints other than the first rotating joint among the n rotating joints.

[0343] Adding the three formulas included in the above dynamic equation can obtain Formula 6:

[0344]

[0345] Combining in Formula 6 into obtains Formula 7:

[0346]

[0347] Using Formula 5 for Perform equivalent substitution to obtain Equation 8:

[0348]

[0349] Obtain Equation 9 for representing through Equation 8:

[0350]

[0351] Obtain Equation 10 for representing through Equations 5 and 9:

[0352]

[0353] Simultaneously solve to obtain the state equation in matrix form:

[0354]

[0355] where

[0356] I is the identity matrix.

[0357] Optionally, the system stability criterion is related to the state equation determined according to the dynamic equation and the sliding mode surface. Exemplarily, the stability criterion is related to the coefficient matrix in the state equation. To ensure that the system stability criterion is satisfied, the sliding mode parameters need to satisfy the coefficient matrix of the state equation:

[0358] All the characteristic roots are distributed in the left half plane of the complex plane. This state equation can be used as a matrix inequality constraint, that is, the values of the sliding mode parameters are distributed in the left half plane of the complex plane of the coefficient matrix.

[0359] Optionally, in the balance control process of the present application, the robust controller determines the driving torques of n rotating joints according to Equation 4 and the state equation. During the balance control process, the robust controller calculates the driving torques τ of n rotating joints according to Equation 4. Equation 4 involves a sliding mode surface matrix s composed of n sliding mode surfaces, the dynamic model parameters in Equation 2, and also involves the sliding mode parameters.

[0360] The robust controller determines the dynamic model parameters by obtaining the state quantities at the first moment and substituting the state quantities at the first moment into the corresponding equations, and creates n sliding mode surfaces. The sliding mode parameters in the sliding mode surfaces satisfy the system stability conditions. Then, while ensuring that the sliding mode parameters satisfy the matrix inequality constraint formed by the above state equation, the robust controller calculates the driving torques τ of n rotating joints based on Equation 4.

[0361] Exemplarily, in the balance control method provided in this application, the sliding mode parameters that satisfy the matrix inequality constraint are first determined, and then n sliding mode surfaces are constructed by the sliding mode parameters. The robust controller determines the state equation according to the dynamic equation and the representation form of the sliding mode surface (at this time, the sliding mode parameters in the sliding mode surface are unknown); when the robust controller determines that the characteristic roots of the coefficient matrix satisfying the state equation are in the left half plane under the system stability condition, the value or value range of the sliding mode parameters is obtained, and the actual value of the sliding mode parameters required in the process of creating the sliding mode surface is obtained; the robust controller substitutes the sliding mode parameters into the sliding mode surface, and calculates the driving torques of n rotating joints according to the sliding mode surface and the dynamic model parameters.

[0362] Exemplarily, in the balance control method provided in this application, the sliding mode parameters corresponding to n sliding mode surfaces are randomly selected within a certain numerical range first, and n sliding mode surfaces are constructed by using these sliding mode parameters, and the driving torques τ of n rotating joints are calculated by formula 4; subsequently, the robust controller verifies whether the four sliding mode parameters satisfy the above matrix inequality constraint. If the four sliding mode parameters all satisfy the above matrix inequality constraint, the driving torques τ of n rotating joints can be used to control n rotating joints; if the n sliding mode parameters do not satisfy the above matrix inequality constraint, the determined driving torques τ of n rotating joints cannot be used.

[0363] The method for determining the sliding mode parameters will be introduced and illustrated through several embodiments below.

[0364] In some embodiments, for the i-th sliding mode surface among the n sliding mode surfaces, the robust controller determines at least two sliding mode parameters, including: determining a first sliding mode parameter from at least one sliding mode parameter in the (2i - 1)-th prediction parameter set, and determining a second sliding mode parameter from at least one sliding mode parameter in the 2i-th prediction parameter set; wherein, the sliding mode parameters included in the (2i - 1)-th prediction parameter set and the 2i-th prediction parameter set respectively satisfy the constraint conditions of the stability criterion.

[0365] In this embodiment, after determining the state at the first moment, the computer device first uses the above state equation as the matrix inequality constraint to determine the solution sets corresponding to the sliding mode parameters required for n sliding mode surfaces respectively, and obtains 2n prediction parameter sets. That is to say, for any one of the 2n prediction parameter sets, the sliding mode parameters in the prediction parameter set satisfy the system stability principle.

[0366] In the process of creating the \(i\)-th sliding mode surface, the first sliding mode parameter among at least two sliding mode parameters is determined from the \((2i - 1)\)-th predicted parameter set, and the second sliding mode parameter among at least two sliding mode parameters is determined from the \(2i\)-th predicted parameter set. The \(i\)-th sliding mode surface is created according to the state quantity at the first moment and the above at least two sliding mode parameters. Subsequently, the robust controller calculates the driving torques of \(n\) rotating joints according to Equation 4 above.

[0367] It should be noted that in this embodiment, the method for determining the sliding mode parameters is introduced by taking the creation of a sliding mode surface using 2 sliding mode parameters as an example. If \(k\) sliding mode parameters are required to create a sliding mode surface, then in the process of creating the \(i\)-th sliding mode surface, one sliding mode parameter needs to be obtained from each of the \(k\) predicted parameter sets corresponding to the \(i\)-th sliding mode surface, resulting in \(k\) sliding mode parameters. In the case where \(k = 2\), it is the method introduced in the above embodiment. \(k\) is a positive integer greater than or equal to 2, and the maximum value of \(k\) is set according to actual needs, which is not limited in this application.

[0368] This method helps to avoid selecting sliding mode parameters that do not satisfy the system stability, which may lead to the inability to control the balance of the wheel-legged robot with the driving torques of \(n\) rotating joints calculated using these sliding mode parameters, improves the usability of the determined driving torques of the rotating joints, helps to avoid the calculations performed when the computer device re-determines the driving torques, and helps to shorten the time-consuming for determining the driving torques of \(n\) rotating joints.

[0369] The calculation process of the forces and torque commands of the whole body joints will be introduced through several embodiments below.

[0370] In some embodiments, step 1340 further includes sub-step 1346: sub-step 1346, calculating the forces and torque commands of the whole body joints according to the driving torque at the second moment.

[0371] In some embodiments, sub-step 1346 includes: calculating the task acceleration of the wheel-legged robot at the second moment according to the driving torques of \(n\) rotating joints, where the task acceleration includes the acceleration related to the center of mass of the wheel-legged robot.

[0372] Optionally, the center of mass of the wheel-legged robot refers to an imaginary point that aggregates all the mass of the wheel-legged robot, and the center of mass of the wheel-legged robot is related to factors such as the mass distribution of each mechanism of the wheel-legged robot and the posture of the wheel-legged robot.

[0373] Optionally, the task acceleration includes, but is not limited to, at least one of the following: the acceleration of the center of mass of the wheel-legged robot in the x-axis, the acceleration of the center of mass of the wheel-legged robot in the y-axis, the acceleration of the center of mass of the wheel-legged robot in the z-axis, the angular acceleration of the center of mass of the wheel-legged robot rotating about the x-axis, the angular acceleration of the center of mass of the wheel-legged robot rotating about the y-axis, and the angular acceleration of the center of mass of the wheel-legged robot rotating about the z-axis. Exemplarily, the task acceleration is observed in the operational space or in the joint space.

[0374] The operational space refers to the space related to the operation task of the wheel-legged robot, and the physical quantities in this operation are observed in the Cartesian coordinate system (world coordinate). The joint space refers to the coordinate system for observing the motion state of the joints. Exemplarily, the physical quantities in the operational space and the physical quantities in the task space can be converted. The position information of a mechanism in the operational space and its position in the joint space can be converted through kinematic formulas, and the velocity in the operational space and the velocity in the joint space are converted through the Jacobian matrix; where the Jacobian matrix is a matrix formed by arranging first-order partial derivatives in a certain way.

[0375] In some embodiments, the task acceleration includes: the acceleration related to the center of mass of the wheel-legged robot during the execution of the operational space task. Optionally, the task acceleration is related to the position of the center of mass of the wheel-legged robot relative to the wheel-legged robot. For the method of determining the task acceleration, please refer to the following text.

[0376] The operational space task can be understood as the task that the wheel-legged robot needs to execute in the operational space. At a certain moment, the operation task that the wheel-legged robot needs to execute is determined according to the motion scenario of the wheel-legged robot. Optionally, there can be multiple operational space tasks that the wheel-legged robot executes at the first moment.

[0377] Exemplarily, the types of operational space tasks include, but are not limited to, at least one of the following: support wheel task, torso vertical direction task, torso attitude task, swing wheel task, center of mass task, etc.; where the support wheel task refers to the task related to the moving wheel in at least one moving wheel of the wheel-legged robot that is in contact with the contact surface, the torso vertical direction task refers to the task of the torso mechanism (which can also be called the body mechanism) of the wheel-legged robot in the z-axis direction of the world coordinate system, the torso attitude task refers to the task related to the Euler angles of the torso mechanism of the wheel-legged robot, and the Euler angles include roll angle, pitch angle, and yaw angle; the swing wheel task refers to the task related to the moving wheel in at least one moving wheel of the wheel-legged robot that is not in contact with the contact surface; the center of mass task refers to the task related to the center of mass of the wheel-legged robot.

[0378] In some embodiments, sub-step 1346 further includes: the whole-body dynamics controller determines the force and torque commands of the whole body joints of the wheel-legged robot at the second moment according to the task acceleration, and the whole body joints include n rotational joints.

[0379] In some embodiments, the whole body joints refer to the active joints in the wheel-legged robot. Optionally, the types of the whole body joints include: rotational joints and linear joints. Exemplarily, the rotational joint corresponds to a rotational motor, and the deflection angle, angular velocity, etc. of the connecting rod connected to the rotational joint are changed by the rotation of the rotational motor. The linear joint corresponds to a linear motor, and the linear motor is used to change the length of the mechanism. For example, the leg mechanism (the first connecting rod) of the wheel-legged robot includes a linear motor, and the length of the leg mechanism can be adjusted by the linear motor.

[0380] In some embodiments, after determining the task acceleration, the observation module sends the task acceleration to the whole-body dynamics controller; the whole-body dynamics controller determines the force and torque commands corresponding to the whole body joints according to the task acceleration. Optionally, if the wheel-legged robot performs multiple operational space tasks at the first moment, in addition to determining the above-mentioned task acceleration related to the center of mass of the wheel-legged robot, it is also necessary to calculate the other task accelerations corresponding to each of the other operational space tasks. For the specific content of this process, please refer to the embodiments below.

[0381] Optionally, the whole-body dynamics equation of the wheel-legged robot is designed in the whole-body dynamics controller, and the whole-body dynamics equation is used to characterize the relationship between the posture of the wheel-legged robot and the whole-body state variables. The whole-body dynamics equation is obtained by establishing the whole-body dynamics model of the wheel-legged robot and through kinematic derivation.

[0382] Optionally, the whole-body dynamics model can be expressed by the following formula:

[0383]

[0384] Where represents the joint space inertia matrix, and the joint space inertia matrix H includes the inertia of the joint rigid bodies of the whole body joints; represents the offset forces respectively received by the whole body joints in the joint space. The C matrix includes the sum of the Coriolis force, centripetal force, and gravity received by the complete wheel-legged robot; represents the selection matrix; represents the contact point Jacobian matrix; represents the contact force vector, including at least one contact force received by the wheel-legged robot; q, respectively represent the generalized position, generalized velocity, and generalized acceleration; N GDenotes the total degrees of freedom of the robot, N G = N f + N J , N f is the floating degrees of freedom, N J is the degrees of freedom of the active joints. An active joint refers to a joint that can move automatically, N C Denotes the number of contact forces, N C is equal to the number of contact points n C and the dimension N of a single contact force D ∈ {0, 1, 2, 3}. It should be noted that τ is a vector including the forces and torque commands of all body joints, and τ is a vector including the rotational torques of n rotational joints. The two meanings are not the same.

[0385] Optionally, the whole-body dynamics equation is obtained by constructing a whole-body dynamics model of the wheel-legged robot based on rigid-body dynamics. The whole-body dynamics equation is used to describe the relationship between the posture of the complete wheel-legged robot, the motion states of each active joint, and the external forces received.

[0386] In some embodiments, the force and torque commands include at least one of the following commands: force command, torque command. Optionally, the force and torque commands of the rotational motor include a torque command, and the torque command is used to control the rotational motor to rotate according to the torque command; for the force and torque commands of the linear motor, the force command is included, and the force command is used to control the linear motor to perform linear motion.

[0387] The whole-body dynamics controller controls the whole body joints according to the force and torque commands of the whole body joints.

[0388] After determining the force and torque commands of the whole body joints, the whole-body dynamics controller sends the force and torque commands to the joint motors corresponding to the whole body joints respectively. The joint motors corresponding to the whole body joints perform linear motion or rotation according to the received force and torque commands, so that the posture of the wheel-legged robot changes, thereby adjusting the balance state of the wheel-legged robot.

[0389] Optionally, after the rotational motors corresponding to the n rotational motors receive the force and torque commands, the rotational motors rotate to change the deflection angle, angular velocity, and angular acceleration of at least one wheel-legged robot corresponding to the nth-order inverted pendulum model; for the active joints not considered in the nth-order inverted pendulum (i.e., other active joints except the n joints), these active joints start to move after receiving the force and torque commands.

[0390] Exemplarily, after the linear motor in the leg mechanism receives the force and torque commands, the linear motor moves to change the length of the leg mechanism, change the height of the wheel-legged robot, and cause the position of the center of mass of the wheel-legged robot in the z-axis direction to change. Exemplarily, for other rotary motors except for the n rotary motors, the other rotary motors rotate according to the received force and torque commands.

[0391] It should be noted that the rotational torques of the n rotary joints and the numbers of the force and torque commands corresponding to the n rotary joints may be different. In the process of the whole-body dynamics controller determining the force and torque commands of the whole body joints, state quantities related to the operational space task of the wheel-legged robot are used, and more rotary joints are involved.

[0392] The force and torque commands generated by the whole-body dynamics controller are used for balance control, enabling more linkages (more than n linkages) to participate in the balance control, enriching the posture of the wheel-legged robot during the balance adjustment process, and realizing the combination of the balance adjustment and the operational space task of the movement process. The balance adjustment is completed through the combination of the robust controller and the whole-body dynamics controller, providing a new idea for balance control.

[0393] The method for determining the task acceleration will be introduced and illustrated below through several embodiments.

[0394] In some embodiments, the observation module calculates the task acceleration of the wheel-legged robot at the second moment according to the rotational torques of the n rotary joints. Optionally, a method for converting the rotational torques of the n rotary joints into task acceleration is designed in the observation module.

[0395] Optionally, this process may include the following sub-steps:

[0396] The observation module determines the angular acceleration at the second moment according to the dynamic equation and the rotational torques of the n rotary joints.

[0397] This dynamic equation refers to the dynamic equation obtained based on the nth-order inverted pendulum model, which is related to the motion states of the n mechanisms and the rotational torques of the n rotary joints.

[0398] Optionally, after the robust controller of the wheel-legged robot determines the rotational torques of the n rotary joints according to the state quantities at the first moment, it sends the rotational torques of the n rotary joints to the observation module in the control system. The observation module calculates the angular acceleration of the wheel-legged robot at the second moment according to Equation 2 above:

[0399]

[0400] Calculate the angular acceleration of the wheel-legged robot at the second moment.

[0401] Optionally, the angular acceleration at the second moment refers to the angular acceleration related to the n - order inverted pendulum model. Exemplarily, the angular acceleration at the second moment includes the angular accelerations of the n linkages at the second moment and the angular acceleration of the mobile wheels at the second moment.

[0402] Based on the state quantity at the first moment and the angular acceleration at the second moment, the whole - body dynamics controller determines the desired incremental position and the desired incremental velocity of the center of mass of the wheel - legged robot at the second moment. The desired incremental position is used to characterize the distance between the projection of the center of mass of the wheel - legged robot on the contact surface and the virtual contact point in the first direction. The desired incremental velocity is used to characterize the change speed of the above - mentioned distance in the first direction. The virtual contact point refers to the center of all the contact points between the wheel - legged robot and the contact surface.

[0403] In some embodiments, when at least two mobile wheels of the wheel - legged robot are in contact with the contact surface, the virtual contact point refers to the center of the connection line of the contact points between the at least two mobile wheels and the contact surface.

[0404] In some embodiments, the desired position increment is used to characterize the position of the center of mass of the wheel - legged robot relative to the wheel - legged robot. The desired incremental velocity is the first - order derivative of the desired position increment with respect to time, that is, the desired position increment is used to characterize the position change speed of the center of mass of the legged robot relative to the wheel - legged robot.

[0405] Optionally, the desired position increment and the desired velocity increment respectively refer to the relative position and the relative velocity of the center of mass of the wheel - legged robot in the first direction. The first direction refers to the forward direction of the wheel - legged robot (i.e., the x - axis direction in the world coordinate system). If the wheel - legged robot involves motion in the left - right direction (i.e., the y - axis direction in the world coordinate system), then the desired velocity increment refers to the component of the relative velocity of the center of mass of the wheel - legged robot in the first direction.

[0406] In some embodiments, after determining the angular acceleration at the second moment, the observation module determines the desired incremental position and the desired incremental velocity of the center of mass of the wheel - legged robot at the second moment by using the forward kinematics method based on the acceleration at the second moment, the deflection angles of the n linkages, the rotation angles of the mobile wheels, the angular velocities of the n linkages, the configuration, the model, and the parameters of the wheel - legged robot.

[0407] Optionally, when the state quantities such as the acceleration at the second moment, the deflection angles of the n mechanisms, the rotation angles of the mobile wheels, and the angular velocities of the n mechanisms are known, the position and velocity of the end of the wheel - legged robot are calculated according to the forward kinematics, that is, the posture of the wheel - legged robot at the second moment is determined. According to the position of the wheel - legged robot in the operating space and the posture of the wheel - legged robot, the position of the center of mass of the wheel - legged robot in the operating space can be calculated, so as to obtain the desired incremental position and the desired incremental velocity.

[0408] The whole-body dynamics controller determines the task acceleration of the wheel-legged robot at the second moment according to the desired incremental position and the desired incremental velocity.

[0409] In some embodiments, the observation module determines a reference state variable group of the center of mass of the wheel-legged robot according to the desired incremental position and the desired incremental velocity; the observation module determines the task acceleration according to the reference state variable group and the actual state variable group of the center of mass of the legged robot.

[0410] Among them, the reference state variable group is used to characterize: the state variables of the center of mass of the wheel-legged robot deduced by kinematics at the second moment. Optionally, the reference state variable group includes: the desired incremental position Δx r and the desired incremental velocity the desired position the desired velocity The desired position refers to the operating space position of the center of mass of the wheel-legged robot at the second moment, or the joint space position at the second moment. The desired velocity is the first derivative of the desired position with respect to time.

[0411] The actual state variable group is used to characterize: the state variables of the wheel-legged robot obtained by sensor observation. Optionally, the actual state variable group includes: the actual incremental position Δx a and the actual incremental velocity the actual position the actual velocity The actual position refers to the operating space position of the center of mass of the wheel-legged robot, and the actual velocity is the first derivative of the actual position with respect to time.

[0412] Optionally, the task acceleration of the wheel-legged robot at the second moment can be calculated by the following formula:

[0413]

[0414] Among them, K represents the state feedback gain matrix. Exemplarily, the objective function of the inverted pendulum dynamics equation is constructed by using LQR, and then, with the goal of minimizing the objective function, the feedback gain matrix of the inverted pendulum dynamics equation is iteratively obtained. LQR is constructed based on the quadratic programming optimization method (Quadratic Programming), and its essence is: under linear constraint conditions, find a multi-dimensional vector such that the quadratic form objective function of this multi-dimensional vector is minimized (or maximized).

[0415] In some embodiments, the observation module sends the calculated task acceleration of the wheel-legged robot to the whole-body dynamics controller. The whole-body dynamics controller generates force and torque commands for the whole body joints of the wheel-legged robot according to the task acceleration. The whole-body dynamics controller sends the force and torque commands of the whole body joints to the joint motors corresponding to each active joint, so as to control the movement of the whole body joints, thereby adjusting the posture of the wheel-legged robot to keep the wheel-legged robot in a balanced state.

[0416] In some embodiments, the observation module generates force and torque commands for the whole body joints of the wheel-legged robot according to the task acceleration, including the following steps: The whole-body dynamics controller determines the desired operation space task of the wheel-legged robot at the second moment. The desired operation space task includes at least one task acceleration corresponding to the operation space task; the whole-body dynamics controller performs a space transformation on the desired operation space task to obtain the desired joint space task; the whole-body dynamics controller substitutes the desired joint space task into the whole-body dynamics equation of the wheel-legged robot to obtain the force and torque commands of the whole body joints.

[0417] Optionally, the desired operation space task includes the task acceleration at the second moment. The desired operation space task can be expressed as:

[0418]

[0419] where, refers to the first acceleration corresponding to the support wheel task, refers to the second acceleration corresponding to the task in the vertical direction of the torso, refers to the third acceleration corresponding to the torso posture task, the fourth acceleration corresponding to the swing wheel task, refers to the task acceleration corresponding to the center of mass task. Optionally, the operation space tasks of the wheel-legged robot at different moments are different, that is, the values of some accelerations included in the desired operation space task can be 0.

[0420] Optionally, the relationship between the acceleration in the operation space included in the desired operation space task and the joint space velocity and acceleration in the joint space task is:

[0421]

[0422] where J t represents the Jacobian matrix of the operation space task, represents the derivative of the number of the Jacobian matrix of the operation space task.

[0423] According to the whole-body dynamics equation: and the desired joint space task it is possible to calculate Among them, τ represents the force and torque commands of the whole body joints.

[0424] In order to improve the rationality of the force and torque commands of the whole body joints, at least one constraint condition is added in the process of solving the whole body dynamics equation. The constraint conditions include but are not limited to at least one of the following: joint physical constraints, friction constraints.

[0425] Optionally, the joint physical constraint is used to limit the force and torque commands according to the characteristics of the joint motors corresponding to the whole body joints of the wheel-legged robot. The joint physical constraint can be expressed as:

[0426] τ lb ≤τ≤τ ub

[0427] Among them, τ represents the matrix including the force and torque commands of the whole body joints, and τ lb represents the matrix including the minimum values of the force and torque commands corresponding to each active joint respectively, and τ ub represents the matrix including the maximum values of the force and torque commands corresponding to each active joint respectively.

[0428] Optionally, the friction constraint means that the contact force f at the i-th contact point i should satisfy the friction cone constraint. To reduce the non-linearity, the friction cone can be approximated as a friction angle cone, and the friction force inequality constraint is expressed as:

[0429]

[0430] Among them, n x 、n y 、n z respectively represent the unit orthogonal bases along the contact surface in the operation space system, μ i represents the friction coefficient, and f i,zlb 、f i,zub respectively represent the minimum value and the maximum value of the non-negative normal pressure perpendicular to the contact surface.

[0431] The following introduces the process of solving the whole body dynamics equation. Optionally, this process can be completed by an optimizer: represent the whole body dynamics equation in the form of AX = B for polynomial solution.

[0432] Among them, Using a quadratic programming optimizer, construct an objective function, and the objective function can be expressed as: J = min(AX - B) T Q(AX - B)+X T RX; where Q and R are weight matrices, calculate the minimum value of the objective function through the quadratic programming optimizer, and obtain For each variable in it, the force and torque commands τ of all body joints are thus obtained.

[0433] Through this method, the force and torque commands corresponding to each body joint can be independently determined. In a scenario where multiple real wheels of a wheel-legged robot do not overlap in the first direction, the control of at least one real wheel and at least one real first rotating joint can also be achieved.

[0434] The determination method of each desired acceleration in the desired operation space task is introduced below. The determination method of each element in the desired operation space task is preset. Optionally, the desired acceleration is determined based on the actual acceleration and the reference acceleration.

[0435] 1. The first acceleration corresponding to the support wheel task Determination method.

[0436] Since the support wheel rolls on the contact surface and there is no relative sliding with the contact surface, the desired acceleration of the support wheel is always equal to 0; the desired acceleration of the support wheel can be expressed as If the wheel-legged robot operates in the four-wheel mode, there are four support wheels, and each support wheel has a task in the x direction. Assuming the support wheels do not leave the ground, the height of the support wheels in the z-axis direction of the world coordinate system is constant. Therefore, the tasks of the four support wheels in the z-axis direction are not considered for the time being. Assuming that the wheel-legged robot does not perform left and right turning actions and the translational movement of the wheel-legged robot along the y-axis direction of the world coordinate system in the four-wheel mode, the tasks of the four support wheels in the y-axis direction are not considered for the time being.

[0437] If the wheel-legged robot operates in the two-wheel balance mode, there are two support wheels, and the other two moving wheels are swing wheels. The tasks of the support wheels are not considered for the time being. The tasks related to the two supports are already included in the introduction related to the "center of mass task" below. At the same time, the tasks of the two swing wheels include two dimensions in the x-axis direction and the z-axis direction. If the left and right turning actions of the wheel-legged robot in the two-wheel balance mode and the translational movement of the wheel-legged robot along the y-axis direction are not considered, the tasks of the two swing wheels in the y direction are not considered for the time being.

[0438] 2. The second acceleration corresponding to the task in the vertical direction of the torso Determination method.

[0439] The camera in the wheel-legged robot obtains the position information of the support wheels at multiple future moments by shooting the height change of the contact surface in the line of sight. Through planning methods such as spline curve interpolation, the expression formula of the position information at multiple future moments is determined, and the reference position speed acceleration According to the IMU sensor, the deflection angle (joint angle) and angular velocity of the mechanism, the actual position of the torso mechanism in the vertical direction is calculated through forward kinematics Velocity Construct a PD (Proportional Derivative) feedback controller corresponding to the torso vertical direction task, and calculate the desired acceleration in the torso vertical direction, that is, the second acceleration

[0440]

[0441] 3. The determination method of the third acceleration corresponding to the torso attitude task of the method

[0442] In some scenarios (such as going up stairs), the torso mechanism of the wheel-legged robot needs to be kept as vertical as possible, and the torso mechanism does not rotate, that is, the reference trajectories of the Euler angles composed of the roll angle, pitch angle, and yaw angle of the torso mechanism are all zero, that is The wheel-legged robot calculates the actual Euler angle according to the forward kinematic formula based on the observation results of the IMU sensor Angular velocity Through the PD feedback controller corresponding to the torso attitude task, the desired attitude angular acceleration of the torso can be calculated: that is, the third acceleration

[0443]

[0444] 4. The determination method of the fourth acceleration corresponding to the swing wheel task of the method

[0445] In the scenario of two-wheel balance, for example, when two-wheel balance is driving on the ground, the two swing wheels are required to present specific postures and actions, or there is a switching process between the supporting wheel legs and the swing wheel legs during the process of the two wheels stepping forward on the ground, or there is a switching between the supporting wheel legs and the swing wheel legs during the process of stepping up and down stairs, etc. There is a corresponding fourth acceleration in such scenarios

[0446] The reference position of the swing wheel in the operating space is planned by the method of spline curve interpolation Velocity Acceleration Based on the observation results of the IMU sensor, joint angle and angular velocity information, the actual position of the swing wheel is calculated according to forward kinematics Velocity By constructing a PD feedback controller corresponding to the swing wheel task, the desired acceleration of the swing wheel can be calculated: that is, the third acceleration This PD feedback controller calculates the third acceleration The formula is as follows:

[0447]

[0448] 5. Task acceleration corresponding to the centroid task Determination method.

[0449] Optionally, a reference position of the centroid along the forward direction is planned by a heuristic or model-based method Speed During the movement of the wheel-legged robot, the execution centroid of the wheel-legged robot not only needs to move continuously along the forward direction, but also needs to be within the range where the wheel-legged robot maintains dynamic balance. Based on this, a determination method for the desired acceleration (i.e., task acceleration) of the centroid is designed.

[0450] Assume that the mass of the wheel-legged robot is concentrated at the centroid of the wheel-legged robot. Let the center of the connection line of at least two supporting wheels be the virtual contact point between the inverted pendulum related to the centroid and the contact surface. Connect the centroid and the virtual contact point to construct an inverted pendulum model of the centroid.

[0451] Figure 14 It is a schematic diagram of an inverted pendulum related to the centroid provided by an exemplary embodiment of the present application.

[0452] The centroid 1410 of the wheel-legged robot, the virtual contact point 1420. According to this inverted pendulum model related to the centroid, determine the dynamic equation related to the centroid:

[0453]

[0454] Using a linear quadratic regulator, determine the feedback gain matrix K. Based on the LQR controller, the input of the state equation can be obtained:

[0455] Among them, represents the actual state variable group, represents the actual state variable group. For other parameters, please refer to the above introduction and will not be elaborated here.

[0456] In some embodiments, the balance control method provided by the present application is continuously executed during the operation of the wheel-legged robot. That is, the robust controller continuously obtains the state quantity at the current moment, and determines the dynamic model parameters, establishes a sliding mode surface according to the state quantity at the current moment, and controls the driving torque of n rotating joints according to the dynamic model parameters and the sliding mode surface.

[0457] In some other embodiments, when the IMU sensor detects a drastic change in the deflection angle of some linkages in a wheel-legged robot, the robust controller executes the balance control method starting from step 1310. For example, if at a certain moment the IMU sensor detects that the change in the deflection angle of the first linkage is greater than the angle threshold, the IMU sensor sends the detected state parameters to the robust controller, and the robust controller starts the balance adjustment process. The angle threshold can be preset.

[0458] In some other embodiments, when the moving wheel does not receive the control signal from the controller and the motor encoder detects that the moving wheel has moved, the robust controller starts to execute the balance control method starting from step 1310.

[0459] By this method, the robust controller intermittently performs balance control on the wheel-legged robot, which helps to save the energy consumption of the wheel-legged robot and improve the anti-external interference ability of the wheel-legged robot without significantly affecting the balance control effect.

[0460] The following introduces and illustrates the process of the balance control method through another example:

[0461] During the balance control process, step A10: The robust controller obtains the actual state quantity at the first moment t i of.

[0462] Step A20: Process the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment. Optionally, this step is implemented through the following sub-steps: Processing the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment includes: superimposing the angular velocities of at least two moving wheels in the actual state quantity to obtain the angular velocity of the wheels; determining the geometric relationship between at least two leg mechanisms according to the lengths and deflection angles of at least two leg mechanisms; determining the deflection angle and angular velocity of the first linkage according to the geometric relationship, the deflection angles of at least two leg mechanisms, and the angular velocities of at least two leg mechanisms; taking the deflection angles of n - 1 linkages in the actual state quantity as the deflection angles of n - 1 linkages in the equivalent state quantity; taking the angular velocities of n - 1 linkages in the actual state quantity as the angular velocities of n - 1 linkages in the equivalent state quantity.

[0463] Step A30: The robust controller calculates the driving torque at the second moment according to the dynamic equation and the sliding mode surface. The driving torque at the second moment includes: the driving torques of n rotating joints.

[0464] Step A40: Calculate the force and torque commands of the whole body joints according to the driving torque at the second moment.

[0465] Optionally, this step includes the following sub-steps: The robust controller sends the driving torques of the n rotating joints to the observation module, and the observation module determines the task acceleration based on the driving torques of the n rotating joints; the observation module sends the task acceleration to the whole-body dynamics controller, and the whole-body dynamics controller determines the force and torque commands of the whole body joints according to the task acceleration, and the whole-body dynamics controller sends the corresponding force and torque commands to each joint motor.

[0466] Step A50: At the second moment, the whole-body dynamics controller controls the n-1 rotating joints and the real first joint corresponding to the first rotating joint according to the force and torque commands of the whole body joints

[0467] Step A60: At the second moment t i+1 , the wheel-legged robot controls the motors corresponding to the whole body joints according to the force and torque commands, and adjusts the posture of the wheel-legged robot.

[0468] Before the balance control process ends, the above steps A10-A60 are repeatedly executed.

[0469] It should be noted that all the formulas used in this example are the formulas that appear in the above embodiments. For the parameter explanations in these formulas, please refer to the above embodiments and will not be elaborated here.

[0470] By abstracting the wheel-legged robot into an n-order inverted pendulum model, calculating the driving torques of the n rotating joints, and determining the task acceleration of the wheel-legged robot according to the driving torques of the n rotating joints, the input of the whole-body dynamics controller in the balance control process is obtained, so that the whole-body dynamics controller can calculate the force and torque commands of the whole body joints, enabling each mechanism in the wheel-legged robot to participate in the balance control process, further enriching the posture of the wheel-legged robot in the balance control process, and helping to improve the robustness of the balance control method.

[0471] Next, taking n equal to 2 as an example, some steps in the balance control method will be introduced and explained.

[0472] First, the method for determining the dynamic model parameters will be described

[0473] When n is equal to 2, after abstracting the wheel-legged robot into a second-order inverted pendulum model, the dynamic equation used in the balance control process derived based on the Euler-Lagrange equation can be expressed as:

[0474]

[0475] Optionally, the dynamic model parameters are derived and determined according to the second-order inverted pendulum model for balance control; the dynamic model parameters include: a proportional parameter matrix and an offset parameter matrix.

[0476] In the design process of the robust controller, by performing partial linearization on the dynamic equation:

[0477]

[0478] After processing, formula a is obtained:

[0479]

[0480] Among them, M -1 (α, β) is the inverse matrix of the inertia matrix, M -1 (α, β) * M(α, β) = E, where E is the identity matrix. For the physical meanings of other parameters in the equation, please refer to the above embodiments and will not be elaborated here.

[0481] Process formula a to unify the driving torque τ1 of the first rotating joint and the driving torque τ2 of the second rotating joint in formula a. Use the selection matrix to process formula a to obtain formula b:

[0482]

[0483] Among them, is the offset parameter matrix f[], is the proportional parameter matrix g[], S T is the transpose matrix of matrix S, S T The matrix is a 3*2 selection matrix. For example, S T The matrix is specifically

[0484] Formula b can be pre-designed after the wheel-legged robot is abstracted into a second-order inverted pendulum model. During the process of the balance control method, after the robust controller obtains the state quantity at the first moment, substitute the state quantity at the first moment into the dynamic equation to determine the inertia matrix, the bias force matrix, and the gravity matrix at the first moment; according to the inertia matrix, the bias force matrix, and the gravity matrix, determine the dynamic model parameters.

[0485] The robust controller uses the selection matrix to process the products between the inverse matrix of the inertia matrix and the bias force matrix, and between the inverse matrix of the inertia matrix and the gravity matrix respectively, to obtain the offset parameter matrix. The selection matrix is used to extract the driving torque of the first joint and the driving torque of the second joint from the dynamic equation; the robust controller uses the selection matrix to process the inverse matrix of the inertia matrix to obtain the proportional parameter matrix. For the specific content of this process, please refer to the above embodiments and will not be elaborated here.

[0486] Next, the method for establishing the sliding surface under the second-order inverted pendulum model will be introduced and described.

[0487] Based on the equivalent state quantity at the first moment, the robust controller establishes a sliding mode surface, and the state quantity of the wheel-legged robot gradually approaches 0 on the sliding mode surface.

[0488] In the case where n is equal to 2, it is necessary to determine the driving torque of the first rotating joint and the driving torque of the second rotating joint, and the robust controller needs to establish two sliding mode surfaces. These two sliding mode surfaces include: 1. The sliding mode surface of the first rotating joint, that is, the state quantity related to the first rotating joint gradually approaches 0 on this sliding mode surface; 2. The sliding mode surface of the second rotating joint, that is, the state quantity related to the second rotating joint gradually approaches 0 on this sliding mode surface.

[0489] Optionally, the first sliding mode surface is different from the second sliding mode surface. The purpose of setting the first sliding mode surface and the second sliding mode surface is to calculate the driving torque of the first rotating joint and the driving torque of the second rotating joint, and the first sliding mode surface and the second sliding mode surface jointly participate in the calculation process of the driving torque of the first rotating joint and the second rotating joint. The definition of the first sliding mode surface may not be limited to being the sliding mode surface corresponding to the first rotating joint. Similarly, the definition of the second sliding mode surface may not be limited to being the sliding mode surface corresponding to the second rotating joint. The first sliding mode surface and the second sliding mode surface can be defined according to actual needs, and this application does not limit them here.

[0490] As can be seen from the introduction of the n-order inverted pendulum model above, in order to ensure that the determined driving torque is calculated, at least 3 state parameters and at least 2 sliding mode parameters in the state quantity are required to establish the sliding mode surface; among them, the equivalent state quantity is written as Then α, β, are all state parameters.

[0491] The robust controller determines at least four sliding mode parameters, and the sliding mode parameters are used to constrain the driving torque of the first joint and the driving torque of the second joint to meet the system stability conditions of the wheel-legged robot.

[0492] Optionally, the state parameters and the sliding mode parameters used for establishing different sliding mode surfaces are different respectively. Exemplarily, to establish the first sliding mode surface, at least the deflection angle of the leg mechanism, the angular velocity of the moving wheel, and the angular velocity of the leg mechanism in the equivalent state quantity are required; to establish the second sliding mode surface, at least the deflection angle of the torso mechanism, the angular velocity of the moving wheel, and the angular velocity of the torso mechanism in the state quantity at the first moment are required; in this case, at least two sliding mode parameters included in the first sliding mode surface are respectively: the sliding mode parameter corresponding to the deflection angle of the leg mechanism, the sliding mode parameter corresponding to the angular velocity of the moving wheel. At least two sliding mode parameters included in the second sliding mode surface are respectively: the sliding mode parameter corresponding to the deflection angle of the torso mechanism, the sliding mode parameter corresponding to the angular velocity of the moving wheel.

[0493] The robust controller establishes a first sliding mode surface and a second sliding mode surface according to the equivalent state quantity at the first moment and at least four sliding mode parameters.

[0494] Optionally, the robust controller establishes a first sliding mode surface according to the first sliding mode parameter, the second sliding mode parameter, the deflection angle of the leg mechanism, the angular velocity of the moving wheel, and the angular velocity of the leg mechanism; and establishes a second sliding mode surface according to the third sliding mode parameter, the fourth sliding mode parameter, the deflection angle of the torso mechanism, the angular velocity of the torso mechanism, and the angular acceleration of the leg mechanism.

[0495] Exemplarily, the robust controller processes the deflection angle of the leg mechanism through the first sliding mode parameter to obtain a processing result of the leg mechanism; processes the angular velocity of the moving wheel through the second sliding mode parameter to obtain a processing result of the moving wheel, and the robust controller determines the first sliding mode surface according to the processing result of the leg mechanism, the processing result of the moving wheel, and the angular velocity of the leg mechanism. Optionally, the first sliding mode surface is proportional to the processing result of the leg mechanism, the first sliding mode surface is proportional to the processing result of the moving wheel, and the first sliding mode surface is proportional to the angular velocity of the leg mechanism.

[0496] For example, the robust controller adds the processing result of the leg mechanism, the processing result of the moving wheel, and the angular velocity of the leg mechanism to obtain the first sliding mode surface.

[0497] Exemplarily, the robust controller processes the deflection angle of the torso mechanism through the third sliding mode parameter to obtain a processing result of the torso mechanism; processes the angular velocity of the moving wheel through the fourth sliding mode parameter to obtain a processing result of the moving wheel; and the robust controller determines the second sliding mode surface according to the processing result of the torso mechanism, the processing result of the moving wheel, and the angular velocity of the torso mechanism. Optionally, the second sliding mode surface is proportional to the processing result of the torso mechanism, the second sliding mode surface is proportional to the processing result of the moving wheel, and the second sliding mode surface is proportional to the angular velocity of the leg mechanism.

[0498] For example, the robust controller adds the processing result of the torso mechanism, the processing result of the moving wheel, and the angular velocity of the torso mechanism to obtain the second sliding mode surface.

[0499] In some embodiments, during the balance control process, the robust controller establishes a first sliding mode surface s1 and a second sliding mode surface s2 according to the following two formulas:

[0500] s1 = λ1ξ1 + λ2ξ3 + ξ4

[0501] s2 = λ3ξ2 + λ4ξ3 + ξ5

[0502] Wherein, λ1 represents the first sliding mode parameter, λ2 represents the second sliding mode parameter, λ3 represents the third sliding mode parameter, λ4 represents the fourth sliding mode parameter, and ξ1 represents the equivalent state quantity The first element α in it, ξ2 represents the equivalent state quantity The second element β in it, ξ3 represents the equivalent state quantity The third element in ξ4 represents the equivalent state quantity The fourth element in ξ5 represents the equivalent state quantity The fifth element in

[0503] By establishing the first sliding mode surface and the second sliding mode surface in this way, and controlling the number of sliding mode parameters in the first and second sliding mode surfaces, the rotational torque of the first joint and the rotational torque of the second joint that meet the system stability principle can be determined with relatively small computational overhead, which helps to improve the speed of determining the rotational torque and achieve the balance control of the robot.

[0504] The method for determining the rotational torque will be introduced and explained below.

[0505] The robust controller calculates the rotational torque of the first rotating joint and the rotational torque of the second rotating joint according to the sliding mode surface and the dynamic model parameters.

[0506] After determining the first sliding mode surface and the second sliding mode surface, the robust controller calculates the first-order derivative formula of the first sliding mode surface s1 with respect to time and the first-order derivative function formula of the second sliding mode surface s2 with respect to time:[[]]

[0507]

[0508]

[0509] Among them,[[]] represents the first-order derivative of the first sliding mode surface s1 with respect to time,[[]] represents the first-order derivative of the second sliding mode surface s2 with respect to time, f k (k ∈ (1, 2, 3)) is the element in the offset parameter matrix f[] in formula 2 above, g mn (m ∈ (1, 2, 3), n ∈ (1, 2, 3)) is the element in the proportional parameter matrix g[] in formula 2 above.

[0510] The first-order derivative formula of the first sliding mode surface s1 with respect to time and the first-order derivative formula of the second sliding mode surface s2 with respect to time are arranged in matrix form to obtain formula c:[[]]

[0511]

[0512] Formula c is transposed to obtain formula d:[[]]

[0513]

[0514] Among them, g s -1 is the inverse matrix of g, sgn() is the sign function, s and

[0515] Formula d can be further written as formula e:

[0516]

[0517] That is, when n = 2 in the n - order inverted pendulum model, formula 4 in the above text is realized as formula d, and formula 5

[0518] is realized as formula e. In the method for balance control based on the second - order inverted pendulum model, the calculation processes of the driving torques of the first rotating joint and the second rotating joint need to use formula d and formula e.

[0519] Optionally, in the calculation process of the driving torque, the robust controller needs to consider the system stability condition. For the method of satisfying the system stability condition in the balance control process of the second - order inverted pendulum model, please refer to the following embodiments.

[0520] For the specific introduction of this content, please refer to the relevant content in the above n - order inverted pendulum model, and it will not be elaborated here.

[0521] In summary, based on abstracting the wheel - legged robot into a second - order inverted pendulum model, during the balance control process, it is possible to adjust the angle between the moving wheel and the leg mechanism, and, adaptively adjust the angle between the torso mechanism and the leg mechanism; enrich the posture of the robot during the balance adjustment process, make the posture change of the robot more flexible, help quickly adjust the robot to the balanced state, improve the ability of the robot to return to the balanced state under different disturbing forces, and enhance the robustness of the robot balance control process.

[0522] The following introduces and illustrates the process of satisfying the system stability criterion during the calculation of the driving torques of the first rotating joint and the second rotating joint through an embodiment.

[0523] It can be known from the definition and properties of the sliding mode surface that the state parameters satisfy on the sliding mode surface:

[0524] s1 = λ1ξ1 + λ2ξ3 + ξ4 = 0

[0525] s2 = λ3ξ2 + λ4ξ3 + ξ5 = 0

[0526] Through the above two formulas, ξ4 and ξ5 can be inversely expressed:

[0527] ξ4 = -λ1ξ1 - λ2ξ3

[0528] ξ5 = -λ3ξ2 - λ4ξ3

[0529] Then the first derivative of ξ4 with respect to time The first derivative of ξ5 with respect to time Can be expressed as:

[0530]

[0531]

[0532] Since ξ4 represents ξ1 represents α, ξ5 represents ξ2 represents β; therefore, ξ1, ξ2 can be expressed by the following formula:

[0533]

[0534]

[0535]

[0536] Recall the dynamic equations of the second-order inverted pendulum model in polynomial form that appeared above:

[0537]

[0538]

[0539]

[0540] Adding the 3 formulas included in the dynamic equation in polynomial form can obtain formula f:

[0541]

[0542] Replace the in formula f to obtain formula g:

[0543]

[0544] Arrange formula g to obtain formula h:

[0545]

[0546] Inverse representation through formula h Obtain:

[0547]

[0548] For those that respectively include The three formulas are combined to obtain equation group 1:

[0549]

[0550] Due to space constraints, Eq. The representation on the right side of the equation is somewhat distorted. The “[]” represents an algebraic expression, not a matrix or other meanings. Please refer to the above equation group 1. The expression can be used to understand the equation 1 The way of expressing.

[0551] The equation group 1 can be written as a state equation about the state variables (ξ1, ξ2, ξ3). Alternatively, the state equation refers to an equation related to the state quantity.

[0552] For ease of reading, a1 is used to represent m1 means m2 means m3 means The state equation can be written as:

[0553]

[0554] Optionally, the system stability criterion refers to that the characteristic roots of the coefficient matrix in the state equation determined according to the sliding surface and the dynamic equation are negative, that is, the characteristic roots are distributed in the left half plane of the phase plane.

[0555] In order to ensure that the system meets the stability criterion, the coefficient matrix needs to be satisfied The characteristic roots of are distributed in the left half plane of the complex plane. This state equation can be used as a matrix inequality constraint, that is, the value of the sliding mode parameter needs to make the characteristic root of the coefficient matrix negative.

[0556] Optionally, in the balancing control process of the present application, the robust controller determines the rotational torque of the first joint and the rotational torque of the second joint according to formula d and equation group 1.

[0557] In the process of balancing control, the robust controller calculates the turning torque τ1 of the first joint and the turning torque τ2 of the second joint according to formula d. Formula d involves the sliding surface s1, the second sliding surface s2, the dynamic model parameters and the sliding parameters in formula 2. The robust controller obtains the state quantity at the first moment from the sensor, and substitutes the state quantity at the first moment into the corresponding formula, determines the sliding surface s1, the second sliding surface s2 and the dynamic model parameters, and finds the sliding parameters that meet the system stability conditions, and then calculates the turning torque τ1 of the first joint and the turning torque τ2 of the second joint by formula d, while ensuring that the sliding parameters meet the matrix inequality constraints formed by the above state equations.

[0558] In the balance control method provided by this application, four sliding mode parameters that satisfy the matrix inequality constraint can be determined first, and then a first sliding mode surface and a second sliding mode surface can be constructed through the sliding mode parameters.

[0559] It is also possible to arbitrarily select four sliding mode parameters within a certain numerical range, use these four sliding mode parameters to construct a first sliding mode surface and a second sliding mode surface, and after calculating the driving torque τ1 of the first joint and the driving torque τ2 of the second joint through formula d, then verify whether the four sliding mode parameters satisfy the above matrix inequality constraint.

[0560] Optionally, when the four sliding mode parameters satisfy the above matrix inequality constraint, the determined driving torque τ1 of the first joint and the driving torque τ2 of the second joint can be used; when the four sliding mode parameters do not satisfy the above matrix inequality constraint, the determined driving torque τ1 of the first joint and the driving torque τ2 of the second joint cannot be used.

[0561] The method for determining the sliding mode parameters will be introduced and illustrated through several embodiments below.

[0562] In some embodiments, determining at least four sliding mode parameters includes: a computer device determining a first sliding mode parameter from a first prediction parameter set, determining a second sliding mode parameter from a second prediction parameter set, determining a third sliding mode parameter from a third prediction parameter set, and determining a fourth sliding mode parameter from a fourth prediction parameter set; wherein, the sliding mode parameters included in the first prediction parameter set, the second prediction parameter set, the third prediction parameter set, and the fourth prediction parameter set respectively satisfy the constraint conditions of the stability criterion.

[0563] In this embodiment, after determining the state at the first moment, the robust controller first takes the above state equation as a matrix inequality constraint, determines the solution sets corresponding to λ1, λ2, λ3, and λ4 respectively, that is, the first prediction parameter set, the second prediction parameter set, the third prediction parameter set, and the fourth prediction parameter set, and then selects the first sliding mode parameter, the second sliding mode parameter, the third sliding mode parameter, and the fourth sliding mode parameter from each parameter set respectively, and through the first sliding mode parameter, the second sliding mode parameter, the third sliding mode parameter, the fourth sliding mode parameter, and the state quantity at the first moment, establish a first sliding mode surface and a second sliding mode surface, and further calculate the driving torque of the first joint and the driving torque of the second joint according to formula d above.

[0564] In some implementations, the process of determining any one of the four prediction solution sets is: calculating the coefficient matrix of the eigenvalues, and all the eigenvalues corresponding to the coefficient matrix are used as the prediction parameter set.

[0565] By this method, it is possible to avoid selecting sliding mode parameters that do not meet the system stability, which may lead to the inability to control the balance of the wheel-legged robot with the rotational torque corresponding to the first joint and the rotational torque corresponding to the second joint calculated using these sliding mode parameters, and avoid invalid calculations by the computer device, which helps to shorten the time required to determine the rotational torque corresponding to the first joint and the rotational torque corresponding to the second joint.

[0566] Next, the robustness control effect of the balance control of the wheel-legged robot under the action of the balance control method provided in this embodiment is experimentally verified.

[0567] Figure 15 It is a simulation schematic diagram of the four-wheel balance control method provided by an exemplary embodiment of the present application.

[0568] Figure 15 In the wheel-legged robot, there are four moving wheels and four leg mechanisms. When the wheel-legged robot is in a four-wheel motion state, the four moving wheels are divided into two forward moving wheels and two backward moving wheels, and the four leg mechanisms are divided into two forward leg mechanisms and two backward leg mechanisms. Balance control is performed during the four-wheel driving process: during a certain process of adjusting the posture of the wheel-legged robot, after the robust controller determines the rotational torques of n rotating joints, the task acceleration is calculated based on the rotational torques of the n rotating joints; the task acceleration is input into the whole-body dynamics controller to obtain the force and torque commands of the whole-body joints output by the whole-body dynamics controller; the whole-body joints of the wheel-legged robot are driven by the force and torque commands of the whole-body joints. Optionally, the included angle between the joints of the n mechanisms can change, and the lengths of the forward leg mechanism and the backward leg mechanism can change, and the speeds of the forward moving wheel and the backward moving wheel can be different. During the balance control process, the distance between the forward moving wheel and the backward moving wheel is changed, that is, the size of the support footprint, until the four wheels of the front and rear moving wheels move to a collinear position, and the wheel-legged robot changes into a state close to two-wheel balance.

[0569] The following is an apparatus embodiment of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the method embodiment of the present application.

[0570] Please refer to Figure 16, which shows a block diagram of a balance control device for a wheel-leg robot provided by an embodiment of the present application. The device has the function of implementing the balance control method of the above-mentioned wheel-leg robot, and the function can be implemented by hardware or by hardware executing corresponding software. The device can be the computer device introduced above or can be set in the computer device. The wheel-leg robot is simplified to an n-order inverted pendulum model, and the n-order inverted pendulum model includes: a wheel, n linkages and n rotating joints. The wheel and the first linkage among the n linkages are connected through the first rotating joint among the n rotating joints. The n linkages are serially connected through n - 1 rotating joints except the first rotating joint. The first linkage is an equivalent linkage corresponding to at least two leg mechanisms of the wheel-leg robot, and the wheel is an equivalent moving wheel corresponding to the moving wheels respectively connected by the at least two leg mechanisms. n is a positive integer greater than or equal to 2; The wheel-leg robot includes: a moving wheel, n linkages and n rotating joints. The moving wheel and the first linkage among the n linkages are connected through the first rotating joint among the n rotating joints. The n linkages are serially connected through n - 1 rotating joints except the first rotating joint. n is a positive integer greater than or equal to 3;

[0571] As Figure 16 shown, the device 1600 may include: a state quantity acquisition module 1610, a state quantity processing module, a sliding mode surface establishment module 1630, an instruction determination module 1640, and a joint control module 1650.

[0572] The state quantity acquisition module 1610 is configured to acquire the actual state quantity of the wheel-leg robot at the first moment. The actual state quantity is used to characterize the motion states of n - 1 linkages, the at least two leg mechanisms, and at least two of the moving wheels. The n - 1 linkages are the other linkages among the n linkages except the first linkage.

[0573] The state quantity processing module 1620 is configured to process the actual state quantity at the first moment to obtain the equivalent state quantity at the first moment. The equivalent state quantity is used to characterize the motion states of the n linkages and the wheel.

[0574] The sliding mode surface establishment module 1630 is configured to establish a sliding mode surface according to the equivalent state quantity at the first moment. The equivalent state quantity gradually approaches 0 on the sliding mode surface.

[0575] The instruction determination module 1640 is configured to determine the force and torque instructions for the whole body joints of the wheel-leg robot according to the sliding mode surface, the equivalent state quantity at the first moment, and the dynamic equation of the wheel-leg robot. The whole body joints include the n rotating joints, and the dynamic equation is established based on the n-order inverted pendulum model.

[0576] The joint control module 1650 is configured to control the n rotating joints according to the force and torque commands of the whole body joints at the second moment.

[0577] In some embodiments, the equivalent state quantity includes: the deflection speed of the n linkages, the angular speed of the n linkages, and the angular speed of the wheels; the state quantity processing module 1620 is configured to superimpose the angular speeds of at least two of the mobile wheels in the actual state quantity to obtain the angular speed of the wheels; determine the geometric relationship between the at least two leg mechanisms according to the lengths and deflection angles of the at least two leg mechanisms; determine the deflection angle and the angular speed of the first linkage according to the geometric relationship, the deflection angles of the at least two leg mechanisms, and the angular speeds of the at least two leg mechanisms; use the deflection angles of the n - 1 linkages in the actual state quantity as the deflection angles of the n - 1 linkages in the equivalent state quantity; and use the angular speeds of the n - 1 linkages in the actual state quantity as the angular speeds of the n - 1 linkages in the equivalent state quantity.

[0578] In some embodiments, the command determination module 1640 includes: a torque determination unit configured to calculate the driving torque at the second moment according to the dynamic equation and the sliding mode surface, and the driving torque at the second moment includes: the driving torques of the n rotating joints; and a command calculation unit configured to calculate the force and torque commands of the whole body joints according to the driving torque at the second moment.

[0579] In some embodiments, the torque determination unit includes: a first speed sub - unit configured to determine the angular acceleration of the wheel - legged robot at the second moment according to the dynamic equation and the driving torque at the second moment, and the angular acceleration at the second moment includes the angular accelerations of the n linkages at the second moment; a second speed sub - unit configured to determine the task acceleration of the wheel - legged robot at the second moment according to the angular acceleration at the second moment, and the task acceleration is related to the acceleration of the centroid of the wheel - legged robot; and a command calculation sub - unit configured to calculate the force and torque commands of the whole body joints according to the task acceleration.

[0580] In some embodiments, the second velocity sub-unit is configured to determine the desired incremental position and the desired incremental velocity of the center of mass of the wheel-legged robot at the second moment according to the equivalent state quantity at the first moment and the angular acceleration at the second moment. The desired incremental position is used to characterize the distance between the projection of the center of mass of the wheel-legged robot on the contact surface and the virtual contact point in the first direction, and the desired incremental velocity is used to characterize the change rate of the distance in the first direction. The virtual contact point refers to the center of each contact point between the wheel-legged robot and the contact surface; according to the desired incremental position and the desired incremental velocity, determine the task acceleration of the wheel-legged robot at the second moment.

[0581] In some embodiments, the torque determination unit includes: a parameter determination sub-unit, configured to determine the dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment, where the dynamic model parameters are used to define the mapping relationship between the angular acceleration at the first moment and the rotational torque at the second moment; the angular acceleration at the first moment includes the angular accelerations of the n linkages; a torque determination sub-unit, configured to calculate the rotational torque at the second moment according to the dynamic parameters and the sliding mode surface.

[0582] In some embodiments, the parameter determination sub-unit is configured to: substitute the equivalent state quantity at the first moment into the dynamic equation to determine the inertia matrix, the centripetal force matrix, and the gravity matrix at the first moment. The inertia matrix is used to characterize the mass and moment of inertia of the n rotational joints at the first moment, the centripetal force matrix is used to characterize the centripetal force of the wheel-legged robot at the first moment, and the gravity matrix is used to characterize the gravity of the wheel-legged robot at the first moment; determine the dynamic model parameters according to the inertia matrix, the centripetal force matrix, and the gravity matrix.

[0583] In some embodiments, the dynamic model parameters include: a proportional parameter matrix and an offset parameter matrix. The proportional parameter matrix is used to characterize the proportional relationship between the angular acceleration at the first moment and the rotational torque at the second moment, and the offset parameter matrix is used to characterize the offset relationship between the angular acceleration at the first moment and the rotational torque at the second moment; the parameter determination sub-unit is configured to use a selection matrix to process the product of the inverse matrix of the inertia matrix and the centripetal force matrix and the product of the inverse matrix of the inertia matrix and the gravity matrix respectively to obtain the offset parameter matrix, where the selection matrix is used to extract the rotational torques of the n rotational joints from the dynamic equation; use the selection matrix to process the inverse matrix of the inertia matrix to obtain the proportional parameter matrix.

[0584] In some embodiments, the sliding mode surface establishing module 1630 includes: a sliding mode determining unit configured to determine at least two sliding mode parameters for the i-th sliding mode surface among the n sliding mode surfaces, where i is a positive integer less than or equal to n; and a sliding mode establishing unit configured to establish the i-th sliding mode surface according to the at least two sliding mode parameters and the equivalent state quantity at the first moment.

[0585] In some embodiments, the sliding mode determining unit is configured to determine a first sliding mode parameter among the at least two sliding mode parameters from the (2i - 1)-th predicted parameter set, and determine a second sliding mode parameter among the at least two sliding mode parameters from the 2i-th predicted parameter set; wherein the sliding mode parameters included in the (2i - 1)-th predicted parameter set and the 2i-th predicted parameter set respectively satisfy the constraint conditions of the stability criterion.

[0586] In some embodiments, the equivalent state quantity includes: the deflection angles of the n linkages, the angular velocities of the n linkages, and the angular velocity of the wheel; the sliding mode establishing unit is configured to process the deflection angle of the i-th linkage according to the first sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the i-th linkage; process the angular velocity of the wheel according to the second sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the wheel; and establish the i-th sliding mode surface according to the processed processing result of the i-th linkage, the processing result of the wheel, and the angular velocity of the i-th linkage.

[0587] In some embodiments, the device 1600 further includes: a motor control unit configured to: for the linear motors in the at least two leg mechanisms, control the linear motors to move according to the force and torque commands of the whole body joints, and the linear motors in the leg mechanisms control the lengths of the leg mechanisms.

[0588] In some embodiments, the virtual contact point of the wheel on the contact surface is located between the contact points of the at least two moving wheels on the contact surface.

[0589] It should be noted that when the device provided in the above embodiments realizes its functions, only the above-mentioned division of each functional module is used for illustration. In practical applications, the above functions can be allocated to different functional modules according to needs, that is, the content structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device provided in the above embodiments and the method embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0590] Please refer to Figure 16, which shows a structural block diagram of a computer device 1600 provided by an embodiment of the present application. The computer device 1600 can be any electronic device with data calculation, processing, and storage functions. The computer device 1600 can be used to implement the balance control method of the wheel-legged robot provided in the above embodiment.

[0591] Generally, the computer device 1600 includes: a processor 1601 and a memory 1602.

[0592] The processor 1601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1601 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), and PLA (Programmable Logic Array). The processor 1601 may also include a main processor and a coprocessor. The main processor is a processor used to process data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 1601 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1601 may also include an AI processor, which is used to process computational operations related to machine learning.

[0593] The memory 1602 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 1602 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1602 is used to store a computer program, and the computer program is configured to be executed by one or more processors to implement the above-mentioned balance control method of the wheel-legged robot.

[0594] Those skilled in the art can understand that Figure 16 the structure shown in

[0595] In a schematic embodiment, a computer-readable storage medium is further provided. A computer program is stored in the storage medium, and when the computer program is executed by a processor of a computer device, the balance control method of the above-mentioned wheel-legged robot is implemented. Optionally, the above-mentioned computer-readable storage medium may be a ROM (Read-Only Memory), a RAM (Random Access Memory), a CD-ROM (Compact Disc Read-Only Memory), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0596] In an exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program, and the computer program is stored in a computer-readable storage medium. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the balance control method of the above-mentioned wheel-legged robot.

[0597] It should be understood that the "plurality" mentioned herein refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. In addition, the step numbers described herein only exemplarily show a possible execution sequence between steps. In some other embodiments, the above steps may not be executed in the order of the numbers. For example, two steps with different numbers are executed simultaneously, or two steps with different numbers are executed in the reverse order of the illustration. The embodiments of the present application do not limit this.

[0598] The above are only exemplary embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A balance control method for a wheel-legged robot, characterized in that, The wheel-leg robot is simplified to an n-order inverted pendulum model, and the n-order inverted pendulum model includes: a wheel, n linkages, and n rotating joints. The wheel and the first linkage among the n linkages are connected through the first rotating joint among the n rotating joints. The n linkages are serially connected through n - 1 rotating joints except the first rotating joint. The first linkage is an equivalent linkage corresponding to at least two leg mechanisms of the wheel-leg robot, and the wheel is an equivalent moving wheel corresponding to the moving wheels respectively connected by the at least two leg mechanisms. n is a positive integer greater than or equal to 2. The method includes: Obtain the actual state quantities of the wheel-leg robot at a first moment, where the actual state quantities are used to characterize the motion states of the n - 1 linkages, the at least two leg mechanisms, and the at least two moving wheels. The n - 1 linkages are the other linkages among the n linkages except the first linkage. Process the actual state quantities at the first moment to obtain the equivalent state quantities at the first moment. The equivalent state quantities are used to characterize the motion states of the n linkages and the wheel. The equivalent state quantities include the deflection angles of the n linkages, the angular velocities of the n linkages, and the angular velocity of the wheel. The deflection angle and the angular velocity of the first linkage are determined based on the geometric relationship between the at least two leg mechanisms, the deflection angles of the at least two leg mechanisms, and the angular velocities of the at least two leg mechanisms. The geometric relationship is determined according to the lengths and deflection angles of the at least two leg mechanisms. The deflection angles of the n - 1 linkages in the equivalent state quantities are the deflection angles of the n - 1 linkages in the actual state quantities, the angular velocities of the n - 1 linkages in the equivalent state quantities are the angular velocities of the n - 1 linkages in the actual state quantities, and the angular velocity of the wheel is obtained by superimposing the angular velocities of the at least two moving wheels in the actual state quantities. According to the equivalent state quantities at the first moment, establish a sliding mode surface, and the equivalent state quantities gradually tend to 0 on the sliding mode surface. According to the sliding mode surface, the equivalent state quantities at the first moment, and the dynamic equation of the wheel-leg robot, determine the force and torque commands for the whole-body joints of the wheel-leg robot. The whole-body joints include the n rotating joints, and the dynamic equation is established based on the n-order inverted pendulum model. At a second moment, control the real rotating joints corresponding to the n - 1 rotating joints and the first rotating joint according to the force and torque commands of the whole-body joints.

2. The method according to claim 1, wherein The step of determining the force and torque commands for the whole-body joints of the wheel-leg robot according to the sliding mode surface, the equivalent state quantities at the first moment, and the dynamic equation of the wheel-leg robot includes: Calculate the driving torque at the second moment according to the dynamic equation and the sliding mode surface. The driving torque at the second moment includes the driving torques of the n rotating joints. Calculate the force and torque commands for the whole-body joints according to the driving torque at the second moment.

3. The method according to claim 2, wherein Calculating the force and torque commands of the whole body joints according to the rotational torque at the second moment includes: Determining the angular acceleration of the wheel-legged robot at the second moment according to the dynamic equation and the rotational torque at the second moment, where the angular acceleration at the second moment includes the angular accelerations of the n linkages at the second moment; Determining the task acceleration of the wheel-legged robot at the second moment according to the angular acceleration at the second moment, where the task acceleration is related to the acceleration of the center of mass of the wheel-legged robot; Calculating the force and torque commands of the whole body joints according to the task acceleration.

4. The method according to claim 3, characterized in that, The determining the task acceleration of the wheel-legged robot at the second moment according to the angular acceleration at the second moment includes: Determining the expected incremental position and expected incremental velocity of the center of mass of the wheel-legged robot at the second moment according to the equivalent state quantity at the first moment and the angular acceleration at the second moment. The expected incremental position is used to characterize the distance between the projection of the center of mass of the wheel-legged robot on the contact surface and the virtual contact point in the first direction, and the expected incremental velocity is used to characterize the change speed of the distance in the first direction. The virtual contact point refers to the center of each contact point between the wheel-legged robot and the contact surface; Determining the task acceleration of the wheel-legged robot at the second moment according to the expected incremental position and expected incremental velocity.

5. The method according to claim 2, wherein The calculating the rotational torque at the second moment according to the dynamic equation and the sliding mode surface includes: Determining the dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment. The dynamic model parameters are used to define the mapping relationship between the angular acceleration at the first moment and the rotational torque at the second moment; the angular acceleration at the first moment includes the angular accelerations of the n linkages; Calculating the rotational torque at the second moment according to the dynamic model parameters and the sliding mode surface.

6. The method according to claim 5, wherein The determining the dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment includes: Substituting the equivalent state quantity at the first moment into the dynamic equation to determine the inertia matrix, the coriolis force matrix, and the gravity matrix at the first moment. The inertia matrix is used to characterize the mass and moment of inertia of the n rotational joints at the first moment, the coriolis force matrix is used to characterize the coriolis force of the wheel-legged robot at the first moment, and the gravity matrix is used to characterize the gravity of the wheel-legged robot at the first moment; Determining the dynamic model parameters according to the inertia matrix, the coriolis force matrix, and the gravity matrix.

7. The method according to claim 6, characterized in that, The dynamic model parameters include: a proportional parameter matrix and an offset parameter matrix. The proportional parameter matrix is used to characterize the proportional relationship between the angular acceleration at the first moment and the rotational torque at the second moment, and the offset parameter matrix is used to characterize the offset relationship between the angular acceleration at the first moment and the rotational torque at the second moment; Determining the dynamic model parameters according to the inertia matrix, the bias force matrix, and the gravity matrix includes: Processing the product between the inverse matrix of the inertia matrix and the bias force matrix and the product between the inverse matrix of the inertia matrix and the gravity matrix respectively using a selection matrix to obtain an offset parameter matrix, where the selection matrix is used to extract the torque of the n rotational joints from the dynamic equation; Processing the inverse matrix of the inertia matrix using the selection matrix to obtain a proportional parameter matrix.

8. The method according to claim 1, wherein The sliding mode surface includes n sliding mode surfaces, and the n sliding mode surfaces are used to constrain the torque of the n rotational joints; Establishing the sliding mode surface according to the equivalent state quantity at the first moment includes: For the i-th sliding mode surface among the n sliding mode surfaces, determining at least two sliding mode parameters, where i is a positive integer less than or equal to n; Establishing the i-th sliding mode surface according to the at least two sliding mode parameters and the equivalent state quantity at the first moment.

9. The method according to claim 8, wherein For the i-th sliding mode surface among the n sliding mode surfaces, determining at least two sliding mode parameters includes: Determining a first sliding mode parameter among the at least two sliding mode parameters from the (2i - 1)-th prediction parameter set, and determining a second sliding mode parameter among the at least two sliding mode parameters from the 2i-th prediction parameter set; Wherein, the sliding mode parameters included in the (2i - 1)-th prediction parameter set and the 2i-th prediction parameter set respectively satisfy the constraint conditions of the stability criterion.

10. The method according to claim 8, wherein Establishing the i-th sliding mode surface according to the at least two sliding mode parameters and the equivalent state quantity at the first moment includes: Processing the deflection angle of the i-th link according to the first sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the i-th link; Processing the angular velocity of the wheel according to the second sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the wheel; Establishing the i-th sliding mode surface according to the processing result of the i-th link, the processing result of the wheel, and the angular velocity of the i-th link.

11. The method according to claim 1, wherein The method further includes: For the linear motors in the at least two leg mechanisms, controlling the linear motors to move according to the force and torque commands of the whole body joints, and the linear motors in the leg mechanisms control the lengths of the leg mechanisms.

12. The method according to any one of claims 1 to 11, characterized in that, The virtual contact point of the wheel on the contact surface is between the contact points of the at least two mobile wheels on the contact surface.

13. A balance control device for a wheel-leg robot, characterized in that, The wheeled-leg robot is simplified to an n-order inverted pendulum model, and the n-order inverted pendulum model includes: a wheel, n links, and n rotational joints. The wheel and the first link among the n links are connected by the first rotational joint among the n rotational joints, and the n links are serially connected by n - 1 rotational joints except the first rotational joint. The first link is an equivalent link corresponding to at least two leg mechanisms of the wheeled-leg robot, and the wheel is an equivalent mobile wheel corresponding to the mobile wheels respectively connected by the at least two leg mechanisms. n is a positive integer greater than or equal to 2; The device includes: A state variable acquisition module, configured to acquire the actual state variables of the wheel-leg robot at a first moment, where the actual state variables are used to characterize the motion states of n-1 linkages, the at least two leg mechanisms, and at least two mobile wheels, and the n-1 linkages are the other linkages among the n linkages except the first linkage; A state variable processing module, configured to process the actual state variables at the first moment to obtain the equivalent state variables at the first moment, where the equivalent state variables are used to characterize the motion states of the n linkages and the wheels, the equivalent state variables include the deflection angles of the n linkages, the angular velocities of the n linkages, and the angular velocities of the wheels, the deflection angle and the angular velocity of the first linkage are determined based on the geometric relationship between the at least two leg mechanisms, the deflection angles of the at least two leg mechanisms, and the angular velocities of the at least two leg mechanisms, the geometric relationship is determined according to the lengths and deflection angles of the at least two leg mechanisms, the deflection angles of the n-1 linkages in the equivalent state variables are the deflection angles of the n-1 linkages in the actual state variables, the angular velocities of the n-1 linkages in the equivalent state variables are the angular velocities of the n-1 linkages in the actual state variables, and the angular velocity of the wheels is obtained by superimposing the angular velocities of the at least two mobile wheels in the actual state variables; A sliding mode surface establishment module, configured to establish a sliding mode surface according to the equivalent state variables at the first moment, where the equivalent state variables gradually tend to 0 on the sliding mode surface; An instruction determination module, configured to determine the force and torque instructions for the whole-body joints of the wheel-leg robot according to the sliding mode surface, the equivalent state variables at the first moment, and the dynamic equation of the wheel-leg robot, where the whole-body joints include the n rotational joints, and the dynamic equation is established based on the nth-order inverted pendulum model; A joint control module, configured to control the n rotational joints at a second moment according to the force and torque instructions of the whole-body joints.

14. The device according to claim 13, characterized in that, The instruction determination module includes: A torque determination unit, configured to calculate the rotational torque at the second moment according to the dynamic equation and the sliding mode surface, where the rotational torque at the second moment includes the rotational torques of the n rotational joints; An instruction calculation unit, configured to calculate the force and torque instructions for the whole-body joints according to the rotational torque at the second moment.

15. The device according to claim 14, wherein The torque determination unit includes: A first velocity sub-unit, configured to determine the angular acceleration of the wheel-leg robot at the second moment according to the dynamic equation and the rotational torque at the second moment, where the angular acceleration at the second moment includes the angular accelerations of the n linkages at the second moment; A second velocity sub-unit, configured to determine the task acceleration of the wheel-leg robot at the second moment according to the angular acceleration at the second moment, where the task acceleration is related to the acceleration of the center of mass of the wheel-leg robot; An instruction calculation sub-unit, configured to calculate the force and torque instructions for the whole-body joints according to the task acceleration.

16. The device according to claim 15, characterized in that, The second velocity sub-unit is configured to: Determine the expected incremental position and expected incremental velocity of the centroid of the wheel-legged robot at the second moment according to the equivalent state quantity at the first moment and the angular acceleration at the second moment. The expected incremental position is used to characterize the distance between the projection of the centroid of the wheel-legged robot on the contact surface and the virtual contact point in the first direction, and the expected incremental velocity is used to characterize the change speed of the distance in the first direction. The virtual contact point refers to the center of each contact point between the wheel-legged robot and the contact surface; Determine the task acceleration of the wheel-legged robot at the second moment according to the expected incremental position and expected incremental velocity.

17. The device according to claim 14, characterized in that, The torque determination unit includes: A parameter determination subunit, configured to determine dynamic model parameters according to the dynamic equation of the wheel-legged robot and the equivalent state quantity at the first moment. The dynamic model parameters are used to define the mapping relationship between the angular acceleration at the first moment and the rotational torque at the second moment; the angular acceleration at the first moment includes the angular accelerations of the n linkages; A torque determination subunit, configured to calculate the rotational torque at the second moment according to the dynamic model parameters and the sliding mode surface.

18. The device according to claim 17, wherein The parameter determination subunit is configured to: Substitute the equivalent state quantity at the first moment into the dynamic equation to determine the inertia matrix, the bias force matrix, and the gravity matrix at the first moment. The inertia matrix is used to characterize the mass and moment of inertia of the n rotational joints at the first moment, the bias force matrix is used to characterize the bias force of the wheel-legged robot at the first moment, and the gravity matrix is used to characterize the gravity of the wheel-legged robot at the first moment; Determine the dynamic model parameters according to the inertia matrix, the bias force matrix, and the gravity matrix.

19. The device according to claim 18, wherein The dynamic model parameters include: a proportional parameter matrix and an offset parameter matrix. The proportional parameter matrix is used to characterize the proportional relationship between the angular acceleration at the first moment and the rotational torque at the second moment, and the offset parameter matrix is used to characterize the offset relationship between the angular acceleration at the first moment and the rotational torque at the second moment; the parameter determination subunit is configured to: Process the product between the inverse matrix of the inertia matrix and the bias force matrix and the product between the inverse matrix of the inertia matrix and the gravity matrix respectively using a selection matrix to obtain the offset parameter matrix. The selection matrix is used to extract the rotational torques of the n rotational joints from the dynamic equation; Process the inverse matrix of the inertia matrix using the selection matrix to obtain the proportional parameter matrix.

20. The device according to claim 13, characterized in that The sliding mode surface includes n sliding mode surfaces, and the n sliding mode surfaces are used to constrain the rotational torques of the n rotational joints; The sliding mode surface establishment module includes: A sliding mode determination unit, configured to determine at least two sliding mode parameters for the i-th sliding mode surface among the n sliding mode surfaces, where i is a positive integer less than or equal to n; A sliding mode establishment unit, configured to establish the i-th sliding mode surface according to the at least two sliding mode parameters and the equivalent state quantity at the first moment.

21. The device according to claim 20, wherein The sliding mode determination unit is configured to: Determine the first sliding mode parameter among the at least two sliding mode parameters from the (2i - 1)-th predicted parameter set, and determine the second sliding mode parameter among the at least two sliding mode parameters from the 2i-th predicted parameter set; Wherein, the sliding mode parameters included in the (2i - 1)-th predicted parameter set and the 2i-th predicted parameter set respectively satisfy the constraint conditions of the stability criterion.

22. The device according to claim 20, characterized in that, The sliding mode establishment unit is configured to: Process the deflection angle of the i-th link according to the first sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the i-th link; Process the angular velocity of the wheel according to the second sliding mode parameter among the at least two sliding mode parameters to obtain a processing result of the wheel; Establish the i-th sliding mode surface according to the processing result of the i-th link, the processing result of the wheel, and the angular velocity of the i-th link.

23. The device according to claim 13, characterized in that, The device further includes: A motor control unit, configured to control the linear motor in the at least two leg mechanisms to move according to the force and torque commands of the whole body joints, and the linear motor in the leg mechanism controls the length of the leg mechanism.

24. The device according to any one of claims 13 to 23, characterized in that The virtual contact point of the wheel on the contact surface is between the contact points of the at least two mobile wheels on the contact surface.

25. A computer device, characterized in that, The computer device includes a processor and a memory, and a computer program is stored in the memory. The computer program is loaded and executed by the processor to implement the balance control method of the wheel-legged robot according to any one of claims 1 to 12.

26. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium. The computer program is loaded and executed by a processor to implement the balance control method of the wheel-legged robot according to any one of claims 1 to 12.

27. A computer program product, characterized in that, The computer program product includes a computer program. The computer program is loaded and executed by a processor to implement the balance control method of the wheel-legged robot according to any one of claims 1 to 12.

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