Dual-wheel foot robot's admittance control method and device and dual-wheel foot robot

Abstract

The application discloses a kind of double-wheel foot robot admittance control method, device and double-wheel foot robot, applied to robot technical field, method includes: based on the initial desired leg length data of each leg and ground contact force carries out admittance control, obtains the target desired leg length data of each leg;Wherein, ground contact force is according to the target motor torque of each leg in last control cycle and is obtained by contact force estimation, the ground contact force of first control cycle is zero;Using the target desired leg length data of each leg, actual leg length data and other control data carries out torque processing, obtains the target motor torque of each leg;According to the target motor torque of each leg, each leg is controlled.The application can promote double-wheel foot robot to adapt to various complex terrains, and keep its head height stability, to effectively improve the control precision of double-wheel foot robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robots, and particularly to a double-wheel-foot robot and a method and device for controlling the robot. BACKGROUND

[0002] A double-wheel-foot robot combines the speed advantage of a wheeled robot and the obstacle-surmounting ability of a foot-type robot, and can move efficiently and flexibly on various complex terrains, thus having a wide application prospect. A current double-wheel-foot robot usually ensures that it will not roll over during movement by fixing a desired leg length and a roll angle direction, so as to improve the stability during movement. However, in actual application, the leg length of the double-wheel-foot robot will affect the stability of the head, and when facing complex terrains such as slopes, the double-wheel-foot robot tends to keep a fixed desired leg length by using a proportional-integral-derivative controller, and ignores the flexible control of the legs, which makes it difficult for the double-wheel-foot robot to keep the head stable under global control, and the legs difficult to adapt to complex terrains, thus causing the control precision of the double-wheel-foot robot to decrease. SUMMARY

[0003] The embodiments of the present application provide a double-wheel-foot robot and a method and device for controlling the robot, which are used to make the double-wheel-foot robot adapt to various complex terrains and keep the head highly stable, thus effectively improving the control precision of the double-wheel-foot robot.

[0004] In one aspect, the embodiments of the present application provide a method for controlling a double-wheel-foot robot, which comprises the following steps:

[0005] Performing admittance control based on initial desired leg length data of each leg and ground contact force to obtain target desired leg length data of each leg; wherein the ground contact force is obtained by contact force estimation according to target motor torque of each leg in a previous control cycle, and the ground contact force in a first control cycle is zero;

[0006] Performing torque processing by using target desired leg length data, actual leg length data and other control data of each leg to obtain target motor torque of each leg;

[0007] Controlling each leg according to the target motor torque of each leg.

[0008] Further, in one embodiment, the admittance control based on the initial desired leg length data of each leg and the ground contact force to obtain the target desired leg length data of each leg comprises: obtaining first processing information of each leg based on the initial desired leg length data of each leg; wherein the first processing information comprises the change acceleration and the change rate of the initial desired leg length data; and obtaining the target desired leg length data of each leg according to the first processing information of each leg and the ground contact force in combination with a preset admittance control equation.

[0009] Further, in one embodiment, the target motor torque comprises a knee joint motor torque and other target motor torque; and the torque processing using the target desired leg length data, the actual leg length data and other control data of each leg to obtain the target motor torque of each leg comprises: torque processing using the target desired leg length data and the actual leg length data of each leg to obtain the knee joint motor torque of each leg; and torque processing using other control data of each leg to obtain the other target motor torque of each leg.

[0010] Further, in one embodiment, the torque processing using the target desired leg length data and the actual leg length data of each leg to obtain the knee joint motor torque of each leg comprises: obtaining second processing information based on the actual leg length data and the target desired leg length data of each leg; wherein the second processing information comprises the change acceleration and the change rate of the target desired leg length data and the change rate of the actual leg length data; obtaining the target output force of each leg according to the second processing information, the actual leg length data and the target desired leg length data of each leg; and obtaining the knee joint motor torque of each leg according to the target output force of each leg.

[0011] Further, in one embodiment, the contact force estimation according to the target motor torque of each leg in the last control cycle comprises: obtaining an equation of the joint space acceleration of each leg with respect to the ground contact force according to the target motor torque of each leg in the last control cycle in combination with the generalized coordinates of the double-wheel-foot robot; performing wheel rolling constraint processing on each leg to obtain the task space acceleration of the contact point of each leg with the ground; and obtaining the ground contact force according to the equation of the joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of the contact point of each leg with the ground.

[0012] Further, in one embodiment, the obtaining the equation of joint space acceleration of each leg with respect to the ground contact force according to the target motor torque of each leg in the last control period and the generalized coordinates of the biped robot comprises: obtaining a dynamic model of the biped robot according to the target motor torque of each leg in the last control period and the generalized coordinates of the biped robot; and performing an inverse processing on a mass matrix in the dynamic model to obtain the equation of joint space acceleration of each leg with respect to the ground contact force.

[0013] Further, in one embodiment, the performing the wheel rolling constraint processing on each leg to obtain the task space acceleration of the contact point between each leg and the ground comprises: obtaining a task space velocity of the contact point between each leg and the ground based on the generalized coordinates of the biped robot; and performing a derivation processing on the task space velocity of the contact point between each leg and the ground to obtain the task space acceleration of the contact point between each leg and the ground.

[0014] Further, in one embodiment, the obtaining the ground contact force according to the equation of joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of the contact point between each leg and the ground comprises: determining the task space acceleration of the contact point between each leg and the ground as zero to obtain a ground rolling constraint state equation of each leg; performing a processing on the ground rolling constraint state equation of each leg to obtain the joint space acceleration of each leg; and obtaining the ground contact force according to the joint space acceleration of each leg and the equation of joint space acceleration of each leg with respect to the ground contact force.

[0015] In another aspect, the embodiments of the present application provide a mobility control device of a biped robot, comprising:

[0016] a mobility controller configured to perform mobility control based on initial desired leg length data of each leg and a ground contact force to obtain target desired leg length data of each leg, wherein the ground contact force is obtained according to target motor torque of each leg in the last control period, and the ground contact force in the first control period is zero;

[0017] a torque processor configured to perform torque processing by using the target desired leg length data, the initial desired leg length data and other control data of each leg to obtain target motor torque of each leg;

[0018] a leg controller configured to perform independent control on each leg according to the target motor torque of each leg.

[0019] In another aspect, the embodiments of the present application provide a biped robot, comprising:

[0020] at least one processor;

[0021] at least one memory for storing at least one program;

[0022] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned admittance control method of the two-wheel-legged robot.

[0023] The beneficial effects of the present application are: to provide an admittance control method, device and two-wheel-legged robot of a two-wheel-legged robot. First, based on the initial desired leg length data of each leg and the ground contact force, the admittance control is performed to obtain the target desired leg length data of each leg; wherein the ground contact force is obtained by contact force estimation according to the target motor torque of each leg in the last control cycle, and the ground contact force in the first control cycle is zero; then, the target motor torque of each leg is obtained by using the target desired leg length data, the actual leg length data and other control data of each leg; finally, each leg is controlled according to the target motor torque of each leg. The present application can promote the two-wheel-legged robot to adapt to various complex terrains and maintain the height stability of its head, thereby effectively improving the control accuracy of the two-wheel-legged robot.

[0024] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be achieved and obtained by the structures particularly pointed out in the specification, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 is a flowchart of an admittance control method of a two-wheel-legged robot provided by the present application;

[0026] Figure 2 is a control principle diagram of a two-wheel-legged robot provided by the present application;

[0027] Figure 3 is an example diagram of a simplified model provided by the present application;

[0028] Figure 4 is an example diagram of a complete modeling of a robot provided by the present application;

[0029] Figure 5 is an example diagram of a ground contact model of a two-wheel-legged robot provided by the present application;

[0030] Figure 6 is a structural diagram of an admittance control device of a two-wheel-legged robot provided by the present application;

[0031] Figure 7is an example diagram of a double-wheel foot robot provided by the present application. DETAILED DESCRIPTION

[0032] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0033] The present application is further described below in combination with the drawings and specific embodiments. The described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0034] In the following description, "some embodiments" are related to a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0036] With the rapid development of robot technology, double-wheel foot robots have attracted widespread attention due to their high adaptability and flexibility in complex terrain. When a robot performs a task, it may need to face various complex road surfaces. Double-wheel foot robots combine the speed advantage of wheeled robots and the maneuvering obstacle-crossing ability of foot robots, and can move efficiently and flexibly in various complex terrains, having wide application prospects.

[0037] The Swiss Federal Institute of Technology made changes to the four-legged robot ANYmal, changed the point foot robot to a motor-driven four-wheel foot robot, and modeled the ground contact rolling constraint to obtain the nonholonomic constraint of the wheel-foot contact point, and finally realized the whole body motion control. Subsequently, the off-line trajectory planning of the Zero Moment Point (ZMP) and the upper planning of the Model Predictive Control (MPC) were realized.

[0038] For the control method of the biped robot, a wheeled inverted pendulum (WIP) model is usually adopted and a linear quadratic regulator (LQR) state feedback is used to realize the control. In addition, another method is to use a whole body motion control algorithm to realize the control. Through a further simplified rolling contact model, the nonholonomic constraint of the contact point is written as a task space control mode, and through a sagittal plane inverted pendulum simplified model, the whole robot moment of inertia is taken as a control task, and the linear quadratic regulator state feedback is taken as a tracking target, to realize a control framework combining the linear quadratic regulator and the whole body motion control, to realize flexible control and a rolling and walking integrated motion mode, which can avoid obstacles by lifting one side of the foot end.

[0039] Therefore, at present, most of the related technologies use a planar inverted pendulum model to realize the modeling of the biped robot, which simplifies the legs of the biped robot as a variable length link to solve. However, this method ignores the kinematics and dynamics characteristics of the robot legs. Moreover, this method more models the biped robot as a fixed base robot, ignoring the floating base nature of the biped robot. The above reasons will lead to a decrease in the modeling accuracy of the biped robot, and limit the motion performance of the biped robot.

[0040] In addition, since the current biped robot lacks control in the depth axis direction, the current biped robot usually fixes the desired leg length and roll angle direction to ensure that it will not roll over when moving, thereby improving the stability when moving. However, in actual applications, the leg length of the biped robot will affect the stability of the head, and when facing complex terrains such as slopes, the biped robot tends to maintain a fixed desired leg length through a proportional-integral-derivative (PID) controller, ignoring the flexible control of the legs, which makes it difficult for the biped robot to maintain the stability of the head under global control, and the legs are difficult to adapt to complex terrains, thereby causing the control accuracy of the biped robot to decrease.

[0041] Therefore, the embodiment of the present application provides a double-wheel-foot robot admittance control method, device and double-wheel-foot robot. Firstly, the embodiment of the present application fully considers the floating base characteristics and leg structure of the double-wheel-foot robot, models the double-wheel-foot robot as a whole floating base model, improves the modeling accuracy of the double-wheel-foot robot, fully considers the mechanical characteristics of the double-wheel-foot robot, and improves the solving effect of the kinematic model of the double-wheel-foot robot. Secondly, the embodiment of the present application estimates the ground contact force based on the above model, judges the terrain condition of the double-wheel-foot robot sole through the estimated ground contact force, and controls the leg admittance of the double-wheel-foot robot, so that the double-wheel-foot robot can adaptively change the leg length based on the terrain condition, ensure that the double-wheel-foot robot can adapt to complex terrain, and improve the stability of the head of the double-wheel-foot robot under global control, thereby effectively improving the control accuracy of the double-wheel-foot robot.

[0042] Firstly, a double-wheel-foot robot admittance control method provided by the embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0043] The double-wheel-foot robot admittance control method provided by the embodiment of the present application can be applied to a terminal, can be applied to a server, and can also be software running in a terminal or a server. The terminal can be a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The server can be a standalone physical server, can be a server cluster or a distributed system composed of multiple physical servers, can be a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (CDN) and basic cloud computing services such as big data and artificial intelligence platforms. In addition, the server can also be a node server in a blockchain network, but is not limited thereto. The blockchain is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism and encryption algorithm.

[0044] Reference Figure 1 , Figure 1 is a flowchart of a double-wheel-foot robot admittance control method provided by the present application. The double-wheel-foot robot is usually provided with two leg parts, i.e., a left leg and a right leg. The admittance control method can include the following steps S101-S103.

[0045] S101, based on the initial desired leg length data of each leg part and the ground contact force, admittance control is performed to obtain the target desired leg length data of each leg part.

[0046] It should be noted that the initial desired leg length data refers to the initial desired leg length, and the target desired leg length data refers to the leg length adjusted by the admittance control. In addition, the ground contact force refers to the contact force between the wheels of each leg and the ground, which is obtained by contact force estimation based on the target motor torque of each leg in the previous control cycle.

[0047] It can be understood that the ground contact force in the first control cycle is defined as zero, which means that the first control cycle will not affect the target desired leg length data, which is equivalent to that only the first control cycle does not participate in the admittance control, and the ground contact force in all subsequent control cycles will be estimated based on the target motor torque of the previous control cycle.

[0048] In this step, according to prior knowledge, when the dual-wheel foot robot encounters uphill terrain, the contact force between the dual-wheel foot robot and the ground will have an upward impact trend; when the dual-wheel foot robot encounters downhill terrain, the contact force between the dual-wheel foot robot and the ground will have a downward trend. Accordingly, this step dynamically adjusts the leg length of the dual-wheel foot robot through the change of the contact force, so as to adapt to complex terrain and ensure stable control of the height of the head. Specifically, this step uses the admittance control method to control the leg length of the left leg and the right leg of the robot, that is, the admittance control is performed based on the initial desired leg length data of each leg and the ground contact force, aiming to correct the initial desired leg length to obtain the target desired leg length data of each leg.

[0049] S102, torque processing is performed on the target desired leg length data, the actual leg length data and other control data of each leg to obtain the target motor torque of each leg.

[0050] It should be noted that the target motor torque refers to the torque of the motor of the joint and the wheel of the leg. In addition, the other control data refers to the data associated with the balance controller, roll angle controller, yaw angle controller and other controllers of the dual-wheel foot robot.

[0051] In this step, after obtaining the target desired leg length data, first, the actual leg length data of the dual-wheel foot robot is obtained; then, torque processing is performed on the target desired leg length data, the actual leg length data and other control data of each leg to determine the target motor torque of each leg, which will be used to control the joint and the wheel of each leg.

[0052] S103, control is performed on each leg according to the target motor torque of each leg.

[0053] In this step, the left leg of the biped robot is controlled based on the target motor torque of the left leg to make the joint motor and the wheel motor of the left leg reach the corresponding motor torque, and the right leg of the biped robot is controlled based on the target motor torque of the right leg to make the joint motor and the wheel motor of the right leg reach the corresponding motor torque, so as to realize the control processing of the biped robot.

[0054] It can be seen that, for the control method of the biped robot, on the one hand, the biped robot can more quickly and accurately perceive the terrain condition of the foot bottom without relying on external perception devices such as laser radar and force sensor, so that the biped robot can adaptively change the leg length based on the terrain condition; on the other hand, the biped robot can exhibit dynamic characteristics similar to a spring-damper system when interacting with complex terrain through the admittance control to realize flexible control of the leg of the biped robot, which enables the biped robot to adjust its motion state on surfaces of different hardness, and promotes the actual leg length of the biped robot to tend to the expected leg length; the embodiment of the application can effectively ensure that the biped robot can adapt to complex terrain, while improving the stability of the head of the biped robot under global control, thereby effectively improving the control accuracy of the biped robot.

[0055] The above steps will be further described below.

[0056] In some embodiments, with reference to Figure 2 , Figure 2 is the control principle diagram of the biped robot provided by the application; in the step S101, the admittance control is performed based on the initial expected leg length data of each leg and the ground contact force to obtain the target expected leg length data of each leg, which can include the following steps S201-S202:

[0057] S201, based on the initial expected leg length data of each leg, first processing information of each leg is obtained; wherein the first processing information includes the change acceleration and the change rate of the initial expected leg length data;

[0058] S202, according to the first processing information of each leg and the ground contact force, the target expected leg length data of each leg is obtained in combination with a preset admittance control equation.

[0059] In the control algorithm of the conventional biped robot, there is rarely a way to flexibly control the legs of the biped robot, which makes it difficult for the biped robot to adapt to complex terrain and unable to ensure the stability of the head of the biped robot when moving, thereby causing the control accuracy of the biped robot to decrease. For the left leg and the right leg of the biped robot, the following admittance control process is performed:

[0060] First, the initial expected leg length data of the leg is differentiated to obtain the first derivative of the initial expected leg length data of the leg as the rate of change of the initial expected leg length data of the leg, and the second derivative of the initial expected leg length data of the leg as the acceleration of change of the initial expected leg length data of the leg, thereby obtaining the first processing information of the leg.

[0061] Then, the admittance control equation shown in the following formula (1) is constructed:

[0062]

[0063] In formula (1), L' represents the adjusted expected leg length of the leg, i.e., the target expected leg length data; leg，d represents the target expected leg length data of the leg; represents the rate of change of the target expected leg length data of the leg; represents the acceleration of change of the target expected leg length data of the leg; L represents the original input leg length of the leg, i.e., the initial expected leg length data; leg，d represents the initial expected leg length data of the leg; represents the rate of change of the initial expected leg length data of the leg; represents the acceleration of change of the initial expected leg length data of the leg; K represents the stiffness coefficient, which determines the degree of change of the leg when subjected to external force; B represents the damping coefficient, which is related to the speed of change of the leg length and affects the absorption and damping effect of the leg on external force; M represents the inertia coefficient, which is related to the acceleration of change of the leg length and affects the acceleration response of the leg to external force; F represents the ground contact force. It can be understood that the rate of change of the leg length data is the first derivative of the leg length data, and the acceleration of change of the leg length data is the second derivative of the leg length data.

[0064] Since the final implementation needs to be performed in the robot host code, in order to ensure the accuracy of leg control, discretization processing needs to be performed. The present embodiment adopts a forward difference equation to perform discretization processing on the admittance control equation shown in the above formula (1), i.e., the rate of change and the acceleration of change of the initial expected leg length data are discretized and substituted into the admittance control equation, and the rate of change and the acceleration of change of the target expected leg length data can also be discretized in the same way and substituted into the admittance control equation. Taking the initial expected leg length data as an example, the discretization process can be represented as the following formula (2):

[0065]

[0066] In formula (2), T represents the sampling time, i.e., the time interval between adjacent two sampling periods; k represents the sampling period, which can be understood as the control period.

[0067] Then, the discretized data is substituted into the admittance control equation shown in the above formula (1), and the Laplace transformation is performed on the admittance control equation, so that the admittance control equation after the Laplace transformation is obtained, as shown in the following formula (3):

[0068] (L′ leg,d -L leg,d )K+(L′ leg,d -L leg,d )Bs+(L′ leg,d -L leg,d )Ms 2 =k ad F (3);

[0069] In formula (3), s represents the Laplace operator; k ad represents a compensation coefficient, which is a parameter set for properly adjusting the compensation ratio of the robot ground contact force and the leg length.

[0070] Finally, by performing parameter transformation on the above admittance control equation after the Laplace transformation, the target expected leg length data shown in the following formula (4) is obtained:

[0071]

[0072] Optionally, the damping coefficient, the inertia coefficient and the stiffness coefficient in the admittance control equation can be calibrated according to actual conditions, which are not specifically limited in the embodiment.

[0073] It should be noted that the external force change mode of the wheel-ground contact point of the double-wheel-legged robot is different when going uphill and downhill. When going uphill, on the basis of the original ground force not changing, there is another external force perpendicular to the slope direction generated by the collision of the wheel with the slope; while going downhill, the double-wheel-legged robot often converts the upward support force into an external force perpendicular to the slope, and the peak values of the two force changes are different. In addition, under the action of gravity, the speed of the double-wheel-legged robot when going downhill will be faster, so the reaction speed required by the double-wheel-legged robot when going downhill will also be faster. Since the external force change of the double-wheel-legged robot is different, and the required reaction time is also different, if the same set of admittance control coefficients is used to control the double-wheel-legged robot when going uphill and downhill, the actual performance of the double-wheel-legged robot will be poor, and situations such as insufficient reaction speed and excessive leg retraction when going downhill will occur. Therefore, different admittance control coefficients are used for targeted control in the embodiment, so that the head of the double-wheel-legged robot can adapt to the uphill and downhill states at the same time.

[0074] Specifically, in the admittance control equation, the damping coefficient, the inertia coefficient and the stiffness coefficient jointly constitute the admittance control coefficient of the admittance control equation, wherein: for the stiffness coefficient K, the stiffness coefficient of the double-wheel-foot robot on the downhill needs to be greater than the stiffness coefficient of the double-wheel-foot robot on the uphill; for the damping coefficient B, the damping coefficient of the double-wheel-foot robot on the downhill needs to be less than the damping coefficient of the double-wheel-foot robot on the uphill; for the inertia coefficient M, it does not require a size relationship, the inertia coefficient of the double-wheel-foot robot on the downhill can be equal to the inertia coefficient of the double-wheel-foot robot on the uphill, of course, the two can also be unequal, but it needs to be noted that the inertia coefficients on the uphill and downhill cannot differ too much, that is, the absolute value of the difference between the inertia coefficient of the double-wheel-foot robot on the downhill and the inertia coefficient of the double-wheel-foot robot on the uphill needs to be less than a preset threshold, in some cases, the inertia coefficient of the double-wheel-foot robot on the downhill can be slightly less than the inertia coefficient of the double-wheel-foot robot on the uphill. In this way, by introducing an adaptive parameter mechanism, different admittance control coefficients are used for different terrains, which can make the double-wheel-foot robot have better adaptability when facing different terrains, and improve the adaptability of the control algorithm and the motion stability of the double-wheel-foot robot.

[0075] For example, the inertia coefficient of the double-wheel-foot robot on the uphill can be 1, the stiffness coefficient can be 0.2, and the damping coefficient can be 5; the inertia coefficient of the double-wheel-foot robot on the downhill can be 0.8, the stiffness coefficient can be 10, and the damping coefficient can be 3, but not limited thereto.

[0076] Optionally, the compensation coefficient can be calibrated according to actual conditions, which is not specifically limited in this embodiment.

[0077] It needs to be noted that the double-wheel-foot robot has different requirements for control dynamic performance on the uphill and the downhill. For example, on the downhill, the response speed of the double-wheel-foot robot is often required to be faster to adapt to the faster speed of the double-wheel-foot robot on the downhill, so as to make the double-wheel-foot robot recover to the target expected leg length data faster. In addition, the peak values of the ground contact force experienced by the double-wheel-foot robot on the uphill and the downhill are different. Accordingly, the compensation coefficient of the double-wheel-foot robot on the downhill needs to be greater than the compensation coefficient of the double-wheel-foot robot on the uphill, so that the double-wheel-foot robot can compensate for the difference in peak values on the downhill.

[0078] Therefore, the embodiment adopts the admittance control mode to perform flexible control on the leg of the biped robot, so that the biped robot can better adapt to the complex terrain and keep the head stable. The biped robot can exhibit the dynamic characteristics of a spring-damper system when interacting with the complex terrain through the admittance control, which enables the biped robot to adjust its motion state on the surface with different hardness, promotes the actual leg length of the biped robot to tend to the expected leg length, better adapts to the complex terrain, and improves the stability of the head under the global control, thereby effectively improving the control accuracy of the biped robot.

[0079] In some embodiments, with reference to Figure 2 The target motor torque can include a knee joint motor torque and other target motor torques; and the implementation process of the target motor torque of each leg in step S102 can include the following steps S301-S302:

[0080] S301, performing torque processing on the target expected leg length data and the actual leg length data of each leg to obtain the knee joint motor torque of each leg;

[0081] S302, performing torque processing on the other control data of each leg to obtain the other target motor torque of each leg.

[0082] It should be noted that the other target motor torque can include but is not limited to a hip joint motor torque, an inside motor torque, an outside motor torque, and a wheel motor torque.

[0083] In the embodiment, the controller of the biped robot is relatively complex, and different controllers are usually used to calculate the torque of the motor of different parts, which includes a balance controller, a height controller, a roll angle controller, a yaw angle controller, etc. The balance controller affects the torque of the wheel motor and the hip joint motor, the height controller affects the knee joint motor torque, the roll angle controller compensates the knee joint motor torque, and the yaw angle controller compensates the wheel motor torque. Finally, the biped robot is controlled based on all the torques. Accordingly, the left leg and the right leg of the biped robot in the embodiment perform the following torque processing process: the target expected leg length data and the actual leg length data of the leg are combined with the height controller to perform torque processing, to obtain the knee joint motor torque of the leg, and the other control data of the leg are combined with the other controllers except the height controller to perform torque processing, to obtain the other joint torques except the knee joint motor torque, such as the hip joint motor torque, the inside motor torque, the outside motor torque, and the wheel motor torque, and further to obtain the target motor torque of the leg. In this way, the control accuracy of the biped robot can be effectively ensured.

[0084] It should be noted that the embodiments of the present application only improve the height controller, and other controllers are prior art, and the specific content (i.e., the specific control mode of other controllers and other control data) can directly refer to the technology in the paper "DIABLO: A 6-DoF Wheeled Bipedal Robot Composed Entirely of Direct-Drive Joints".

[0085] In some embodiments, with reference to Figure 2 In the step S301, the torque processing is performed on the target expected leg length data and the actual leg length data of each leg to obtain the implementation process of the knee joint motor torque of each leg, which can include the following steps S401-S403:

[0086] S401, based on the actual leg length data and the target expected leg length data of each leg, obtaining second processing information; wherein the second processing information includes the change acceleration and the change rate of the target expected leg length data and the change rate of the actual leg length data;

[0087] S402, according to the second processing information, the actual leg length data and the target expected leg length data of each leg, obtaining the target output force of each leg;

[0088] S403, according to the target output force of each leg, obtaining the knee joint motor torque of each leg.

[0089] It should be noted that the target output force refers to the output force of the combination of the proportional-derivative (PD) controller and the feedforward controller, which can be understood as the force required for the leg to change without considering the head mass of the biped robot, and the force is used to adjust the height change according to the input.

[0090] In the embodiments, for the height controller of the biped robot, the input is the target expected leg length data of each leg, and the output is the knee joint motor torque of each leg. Specifically, for the left leg and the right leg of the biped robot, the following process is used to solve the knee joint motor torque:

[0091] First, the actual leg length data of the leg is differentiated to obtain the first derivative of the actual leg length data of the leg as the change rate of the actual leg length data of the leg, and the target expected leg length data of the leg is differentiated to obtain the first derivative of the target expected leg length data of the leg as the change rate of the target expected leg length data of the leg, and the second derivative of the target expected leg length data of the leg is obtained as the change acceleration of the target expected leg length data of the leg, and then the second processing information is obtained.

[0092] Then, based on the second processing information of the leg, the actual leg length data and the target expected leg length data, and in combination with preset proportional differential controller coefficients, a target output force of the leg is obtained, which can be expressed as formula (5) as follows:

[0093]

[0094] In formula (5), ΔF represents the target output force; L' represents the target expected leg length data of the leg; leg，d represents the target expected leg length data of the leg; represents the rate of change of the target expected leg length data of the leg; represents the acceleration of change of the target expected leg length data of the leg; L leg represents the actual leg length data of the leg; represents the rate of change of the actual leg length data of the leg; k p and k d are parameters of the proportional differential controller, which are preset values.

[0095] Finally, based on the target output force of the leg, in combination with the head mass and the head Jacobian matrix of the biped robot, a knee joint motor torque of the leg is obtained, which can be expressed as formula (6) as follows, wherein the head Jacobian matrix refers to a Jacobian matrix for mapping the head lifting force of the biped robot to the knee joint motor torque:

[0096] τ knee = J T (ΔF+m H g) (6);

[0097] In formula (6), τ knee represents the knee joint motor torque of the leg; J T represents the head Jacobian matrix of the biped robot; m H represents the head mass of the biped robot; and g represents the acceleration of gravity.

[0098] It can be seen that, in the embodiment, the target expected leg length data obtained by the admittance control is taken as a reference for the head height control of the biped robot, and in combination with the height controller, the knee joint motor torque of the leg is obtained and processed, so that the accuracy of the knee joint motor torque of the leg is improved, the biped robot is better adapted to complex terrain, and the stability of the head of the biped robot under global control is improved, thereby effectively improving the control precision of the biped robot.

[0099] In some embodiments, for the above ground contact force, the implementation process of estimating the contact force according to the target motor torque of each leg in the last control cycle can include the following steps S501-S503:

[0100] S501, obtaining the equation of joint space acceleration of each leg with respect to the ground contact force according to the target motor torque of each leg in the last control cycle and combining the generalized coordinates of the biped robot;

[0101] S502, performing wheel rolling constraint processing on each leg to obtain the task space acceleration of the contact point between each leg and the ground;

[0102] S503, obtaining the ground contact force according to the equation of joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of the contact point between each leg and the ground.

[0103] It should be noted that the task space acceleration of the contact point between the leg and the ground refers to the acceleration of the end effector of the biped robot moving in the task space.

[0104] In this embodiment, the force received by the left and right wheels of the biped robot in contact with the ground is estimated through the current state of the biped robot to indirectly obtain the current terrain state, thereby facilitating dynamic control of the leg length of the biped robot and promoting the head of the biped robot to be more stable. Specifically,

[0105] In the aspect of ground contact force estimation, for the current control cycle, the following ground contact force estimation process is performed for the left leg and the right leg of the biped robot:

[0106] First, considering the floating base characteristics, kinematic characteristics and dynamic characteristics of the biped robot, based on the target motor torque of the leg in the last control cycle, the equation of joint space acceleration of the leg with respect to the ground contact force is constructed by combining the generalized coordinates of the biped robot (which includes the joint coordinates and the un-driven base coordinates of the biped robot in the inertial coordinate system), which aims to be solved with the subsequent rolling constraint to calculate the contact force between the leg and the ground.

[0107] At the same time, in order to limit the movement of the wheel on the ground, it is necessary to establish the constraint equation of wheel rolling and derive the corresponding constraint force. Accordingly, the wheel rolling constraint processing is performed on the leg to construct the constraint rolling of the leg wheel, and the task space acceleration of the contact point between the leg and the ground, i.e. the velocity constraint, is calculated based on the constraint rolling.

[0108] Then, the equation of joint space acceleration of the leg with respect to the ground contact force and the task space acceleration of the contact point between the leg and the ground are solved to obtain the contact force between the leg and the ground, i.e. the ground contact force.

[0109] Therefore, the embodiment does not need to rely on external sensing devices such as laser radar and force sensors, and can accurately estimate the ground contact force without external sensing, so as to make the biped robot perceive the terrain condition of the foot bottom more quickly and accurately, so that the biped robot can adaptively change the leg length based on the terrain condition and keep the height stability of the head, thereby improving the control accuracy of the biped robot.

[0110] In some embodiments, with reference to Figure 3 and Figure 4 , Figure 3 is an example diagram of a simplified model (one side of the original robot configuration) provided by the present application, Figure 4 is an example diagram of a complete modeling of the robot provided by the present application; the implementation process of the equation of the joint space acceleration of each leg with respect to the ground contact force in the above step S501 can include the following steps S601-S602:

[0111] S601, according to the target motor torque of each leg in the last control period, and combining the generalized coordinates of the biped robot, the dynamics model of the biped robot is obtained;

[0112] S602, the mass matrix in the dynamics model is processed to obtain the equation of the joint space acceleration of each leg with respect to the ground contact force.

[0113] In the embodiment, since the biped robot is a floating base robot, its floating base characteristics need to be fully considered, so the base of the biped robot needs to be regarded as being connected to a six-degree-of-freedom joint. The inertia coordinate system I, the floating base coordinate system B and the wheel coordinate system C are defined, the wheel coordinate system includes the left wheel coordinate system C l and the right wheel coordinate system C r , the floating base coordinate system B is located in the vertical direction of the midpoint of the line connecting the two wheel contact points, and the midpoint of the line connecting the two wheel contact points is defined as point N, and the floating base is defined as point B, as shown in Figure 3 , the red arrow represents the horizontal axis of the coordinate system, the green arrow represents the vertical axis of the coordinate system, and the blue arrow represents the depth axis of the coordinate system, all coordinate systems are oriented along the depth axis (Z) of the ground normal vector, and along the forward direction of the biped robot, and the vertical axis (Y) is defined along the line connecting the two wheel contact points.

[0114] Firstly, the kinematic tree model of the double-wheel foot robot is built, and each joint and rigid rod of the double-wheel foot robot is labeled and coded. Since the leg of the double-wheel foot robot is a closed-loop leg, the existing processing method usually needs to perform additional processing on the closed-loop leg, for example, disconnecting the passive joint and applying a closed-loop constraint. This method is often very complex and unnecessary for the control of the double-wheel foot robot. Therefore, the leg of the double-wheel foot robot is simplified as an open-loop leg, as shown in Figure 3 and Figure 4 by simplifying the model without affecting the experiment, the subsequent efficiency can be effectively improved.

[0115] It should be noted that in Figure 3 and Figure 4 , B is a rigid member of the double-wheel foot robot, J is a connecting joint between the rigid members of the double-wheel foot robot, and the parameters in the figure are defined as shown in Table 1.

[0116] Table 1: Parameter definition

[0117]

[0118]

[0119] Next, according to the above content, the generalized coordinates of the kinematic tree model of the double-wheel foot robot are defined, which include the joint coordinates of the double-wheel foot robot and the un-driven base coordinates in the inertial coordinate system; as shown in the following formula (7):

[0120]

[0121] In formula (7), q represents the generalized coordinates of the double-wheel foot robot, q b ∈R 3 x SO represents the un-driven base coordinates, q j ∈R 6 represents the joint coordinates; in q b , I r IB represents the position vector of point B relative to the origin of the inertial coordinate system I, and is represented in the inertial coordinate system I, the above labeling method is applicable to the subsequent embodiments of the present application, r IB represents the translation of the base of the double-wheel foot robot (if the translation is in the positive direction of the coordinate axis, it is positive, otherwise it is negative); R IB ∈ SO represents the rotation matrix of the double-wheel foot robot; in q jIn the formula (8), q1 to q6 represent generalized coordinates of the left inner motor / hip joint motor, the left outer motor / knee joint motor, the left wheel motor, the right inner motor / hip joint motor, the right outer motor / knee joint motor and the right wheel motor respectively.

[0122] Meanwhile, six motor torques of the double-wheel foot robot are defined as shown in the following formula (8):

[0123]

[0124] In the formula (8), τ represents a torque term; τ a ∈R 6 represents a torque of a driven joint, wherein τ1 to τ6 represent a left inner motor / hip joint motor torque, a left outer motor / knee joint motor torque, a left wheel motor torque, a right inner motor / hip joint motor torque, a right outer motor / knee joint motor torque and a right wheel motor torque respectively.

[0125] Then, for the left leg and the right leg of the double-wheel foot robot, both have: on the basis of the target motor torque of the leg in the last control cycle and the generalized coordinates of the double-wheel foot robot, a dynamic model of the double-wheel foot robot is constructed as shown in the following formula (9):

[0126]

[0127] In the formula (9), H ∈ R 12×12 represents a mass (inertia) matrix; C ∈ R 12 represents a Coriolis term; g represents a gravity acceleration; S ∈ R 12×6 represents a selection matrix; τ represents a torque term; represents a Jacobian matrix common to the double-wheel contact points; F represents a ground contact force; represents a robot joint space acceleration, which is a second-order derivative of the generalized coordinates of the double-wheel foot robot. Among them, the mass matrix, the Coriolis term, the selection matrix, the torque term and the Jacobian matrix common to the double-wheel contact points can be obtained by calculation or the ontology of the double-wheel foot robot. Since the subsequent mobility control is a control for the ground contact force, the construction of the dynamic model here is very critical.

[0128] Finally, the inverse of the mass matrix in the dynamic model shown in the above formula (9) can obtain the equation of the joint space acceleration of the leg with respect to the ground contact force as shown in the following formula (10), which is applicable to a single leg, i.e. the left leg or the right leg. This equation aims to calculate the size of the ground contact force of the left and right ends of the robot by listing the equation of the robot joint space acceleration with respect to the ground contact force and simultaneously with the rolling constraint in the following:

[0129]

[0130] Therefore, the embodiment fully considers the floating base characteristics and the leg structure of the double-wheel biped robot, models the double-wheel biped robot as a whole floating base model, and thus can effectively improve the modeling accuracy of the double-wheel biped robot; at the same time, the embodiment fully considers the mechanical characteristics of the double-wheel biped robot, and thus can effectively improve the solving effect of the kinematic model of the double-wheel biped robot.

[0131] In some embodiments, with reference to Figure 5 , Figure 5 is an example diagram of the ground contact model of the double-wheel biped robot provided in the application; the implementation process of the task space acceleration of the contact point between each leg and the ground in the above step S502 can include the following steps S701-S702:

[0132] S701, based on the generalized coordinates of the double-wheel biped robot, obtaining the task space velocity of the contact point between each leg and the ground;

[0133] S702, performing derivative processing on the task space velocity of the contact point between each leg and the ground to obtain the task space acceleration of the contact point between each leg and the ground.

[0134] In the embodiment, in order to limit the movement of the wheels on the ground, it is necessary to establish the constraint equation of the wheel rolling and derive the corresponding constraint force. According to the contour kinematics (Contour Kinematics) combined with the contour parameter (Contour Parameter) to parameterize the positions of the contact points (i.e., points C l and C r ) of the left and right wheels of the double-wheel biped robot relative to the wheel coordinate system C, and the contour parameter depends on the contact between the wheels and the ground, as shown in Figure 5 , W represents the center position of the wheel, and the coordinates of the contact points of the left and right wheels with the ground are determined by the contour parameter σ. The embodiment assumes that the contact points of the left and right wheels of the robot with the ground are always directly below the center position W of the wheel, and thus the ground normal vector I nAlways vertically upward. In this condition, the embodiment obtains the Jacobian matrix mapping from the joint space velocity of the leg to the task space velocity of the contact point between the leg and the ground, which can be calibrated in advance, and since the generalized coordinates of the double-wheel foot robot are known, the initial velocity constraint, i.e. the task space velocity of the contact point between the leg and the ground, which refers to the speed of the end effector of the double-wheel foot robot moving in the task space and describes the speed and direction of the position change of the end effector in the task space, can be directly calculated, which can be defined in the form of the Jacobian matrix as shown in the following formula (11):

[0135]

[0136] In formula (11), denotes the task space velocity of the contact point between the leg and the ground; denotes the first derivative of the generalized coordinates of the double-wheel foot robot, i.e. the joint space velocity; J C denotes the Jacobian matrix mapping from the joint space velocity of the leg to the task space velocity of the contact point between the leg and the ground.

[0137] Finally, the task space velocity of the contact point between the leg and the ground shown in the above formula (11) is derived to obtain the task space acceleration of the contact point between the leg and the ground shown in the following formula (12), which is the final velocity constraint:

[0138]

[0139] In formula (12), denotes the task space acceleration of the contact point between the leg and the ground, which is the first derivative of the task space velocity of the contact point between the leg and the ground; denotes the first derivative of the Jacobian matrix mapping from the joint velocity of the robot to the task space velocity of the contact point between the leg and the ground.

[0140] In some embodiments, according to the equation of the joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of the contact point between each leg and the ground, the implementation process of the ground contact force obtained in the above step S503 can include the following steps S801-S803:

[0141] S801, the task space acceleration of the contact point between each leg and the ground is determined to be zero to obtain the ground rolling constraint state equation of each leg;

[0142] S802, the ground rolling constraint state equation of each leg is processed to obtain the joint space acceleration of each leg;

[0143] S803, obtaining the ground contact force according to the joint space acceleration of each leg and the equation of the joint space acceleration of each leg with respect to the ground contact force.

[0144] In this embodiment, the ground force estimation based on the dynamic model is used, so that the double-wheel foot robot can indirectly perceive the terrain change through the ground force change. For the left leg and the right leg of the double-wheel foot robot, the following estimation process is as follows:

[0145] First, assuming that the contact of the leg wheel with the ground satisfies the pure rolling state, i.e. the velocity of the contact point of the leg with the ground is 0, the task space acceleration of the contact point of the leg with the ground is determined as zero, the ground rolling constraint state equation of the leg can be obtained, which is shown in the following formula (13):

[0146]

[0147] Then, the ground rolling constraint state equation shown in the above formula (13) is transformed, and the joint space acceleration shown in the following formula (14) can be obtained:

[0148]

[0149] Finally, the joint space acceleration shown in the above formula (14) is substituted into the equation of the joint space acceleration of the leg with respect to the ground contact force shown in the above formula (10), and the ground contact force shown in the following formula (15) can be obtained:

[0150]

[0151] In order to facilitate the understanding of the admittance control method of the double-wheel foot robot of the present application, the actual application scene of the admittance control method of the double-wheel foot robot of the present application is taken as an example for illustration. Referring to Figure 2 In this application scene, the double-wheel foot robot has two legs, i.e. the left leg and the right leg, and the specific implementation of the admittance control method for each leg is as follows:

[0152] S901, leg length estimation:

[0153] In the current control cycle, first, the initial desired leg length data of the leg is differentiated to obtain the first derivative of the initial desired leg length data of the leg as the rate of change of the initial desired leg length data of the leg, and the second derivative of the initial desired leg length data of the leg as the acceleration of change of the initial desired leg length data of the leg; then, the above data is discretized, as shown in the above formula (2), the discretized data is substituted into the admittance control equation as shown in the above formula (1), and the Laplace transform of the admittance control equation is performed, to obtain the Laplace transformed admittance control equation, as shown in the above formula (3); finally, the parameter transformation of the above Laplace transformed admittance control equation is performed, to obtain the target desired leg length data as shown in the following formula (4).

[0154] Among them, for the stiffness coefficient, the stiffness coefficient of the double-wheel foot robot when downhill needs to be greater than the stiffness coefficient of the double-wheel foot robot when uphill; for the damping coefficient, the damping coefficient of the double-wheel foot robot when downhill needs to be less than the damping coefficient of the double-wheel foot robot when uphill; for the inertia coefficient, the absolute value of the difference between the inertia coefficient of the double-wheel foot robot when downhill and the inertia coefficient of the double-wheel foot robot when uphill needs to be less than a preset threshold. In addition, the compensation coefficient of the double-wheel foot robot when downhill needs to be greater than the compensation coefficient of the double-wheel foot robot when uphill.

[0155] S902, torque control:

[0156] In the current control cycle, for the height controller:

[0157] In the current control cycle, first, the actual leg length data of the leg is differentiated to obtain the first derivative of the actual leg length data of the leg as the rate of change of the actual leg length data of the leg, and the target desired leg length data of the leg is differentiated to obtain the first derivative of the target desired leg length data of the leg as the rate of change of the target desired leg length data of the leg, and the second derivative of the target desired leg length data of the leg as the acceleration of change of the target desired leg length data of the leg; then, the above data is substituted into the above formula (5) to obtain the target output force of the leg; thereafter, the target output force of the leg, the head mass of the double-wheel foot robot and the head Jacobian matrix are substituted into the above formula (6) to obtain the knee joint motor torque of the leg.

[0158] In the current control cycle, for other controllers:

[0159] The other control data of the legs are combined with the above-mentioned other controllers except the height controller to process the torques, and other joint torques except the knee joint motor torque are obtained, such as the hip joint motor torque, the medial motor torque, the lateral motor torque, and the wheel motor torque, etc. The technology in the paper "DIABLO: A 6-DoF Wheeled Bipedal Robot Composed Entirely of Direct-Drive Joints" can be directly quoted.

[0160] S903, wheel-foot control:

[0161] In the current control cycle, the left leg of the double wheel-foot robot is controlled based on the target motor torque of the left leg, so that the joint motor and the wheel motor of the left leg reach the corresponding motor torque, and the right leg of the double wheel-foot robot is controlled based on the target motor torque of the right leg, so that the joint motor and the wheel motor of the right leg reach the corresponding motor torque.

[0162] S904, cycle termination judgment:

[0163] In the current control cycle, it is judged whether to end the control of the double wheel-foot robot, for example, when the task of the double wheel-foot robot is completed, the control of the double wheel-foot robot is ended, but not limited to this. If yes, the process is directly ended; otherwise, it is entered into step S05.

[0164] S905, contact force estimation:

[0165] Modeling processing: in the current control cycle, first, the generalized coordinates of the kinematic generation tree model of the double wheel-foot robot are defined, including the joint coordinates and the un-driven base coordinates of the double wheel-foot robot in the inertial coordinate system, and six motor torques of the double wheel-foot robot are defined, which can be the target motor torque in the current control cycle; then, based on the target motor torque of the leg in the last control cycle and the generalized coordinates of the double wheel-foot robot, the dynamic model shown in the above-mentioned formula (9) is constructed; finally, the inverse of the mass matrix in the above-mentioned formula (9) is solved, and the equation of the joint space acceleration of the leg with respect to the ground contact force shown in the above-mentioned formula (10) is obtained.

[0166] Rolling constraint: in the current control period, a Jacobian matrix is obtained from the joint space velocity of the leg to the task space velocity of the contact point between the leg and the ground, which can be pre-calibrated, since the generalized coordinates of the double-wheel robot are known, the initial velocity constraint, i.e., the task space velocity of the contact point between the leg and the ground, can be obtained by formula (11) above, and then the task space acceleration of the contact point between the leg and the ground shown in formula (12) above can be obtained by derivation of the task space velocity of the contact point between the leg and the ground shown in formula (11) above, which is the final velocity constraint.

[0167] Estimation of ground contact force: in the current control period, first, the task space acceleration of the contact point between the leg and the ground is determined to be zero, and the ground rolling constraint state equation of the leg shown in formula (13) above can be obtained; then, the joint space acceleration shown in formula (14) above can be obtained by transformation of the ground rolling constraint state equation shown in formula (13) above; finally, the joint space acceleration shown in formula (14) above is substituted into the equation of the joint space acceleration of the leg with respect to the ground contact force shown in formula (10) above, and the ground contact force shown in formula (15) above can be obtained.

[0168] S906, loop control:

[0169] The ground contact force shown in formula (17) above is determined as the ground contact force of the next control period, the next control period is determined as the current control period, and the loop control is returned to step S01.

[0170] In addition, with reference to Figure 6 , the embodiment of the present application also provides a double-wheel robot admittance control device, which comprises:

[0171] An admittance controller 100 is configured to perform admittance control based on initial desired leg length data of each leg and a ground contact force to obtain target desired leg length data of each leg; wherein the ground contact force is obtained by contact force estimation according to target motor torque of each leg in the last control period, and the ground contact force in the first control period is zero;

[0172] A torque processor 200 is configured to perform torque processing by using the target desired leg length data, the initial desired leg length data and other control data of each leg to obtain target motor torque of each leg;

[0173] A leg controller 300 is configured to independently control each leg according to the target motor torque of each leg.

[0174] The contents in the method embodiments are applicable to the device embodiments, the device embodiments specifically implement the same functions as the method embodiments, and achieve the same beneficial effects as the method embodiments.

[0175] Finally, with reference to Figure 7 The device embodiments also provide a double-wheel foot robot, which includes:

[0176] at least one processor 400;

[0177] at least one memory 500 for storing at least one program;

[0178] When the at least one program is executed by the at least one processor 400, the at least one processor 400 implements the admittance control method of the double-wheel foot robot.

[0179] The memory 500 is a non-transitory network system, which can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory 500 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 500 can optionally include a memory 500 remotely arranged relative to the processor 400, and the remote memory 500 can be connected to the processor 400 through a network. Examples of the network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0180] The memory 500 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 500 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 500 and are called and executed by the processor 400 to implement the method of the embodiments of the present application.

[0181] The processor 400 can be implemented in the form of a general-purpose central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0182] In some embodiments, the vehicle can further include:

[0183] The input / output interface is used for realizing information input and output.

[0184] The communication interface is used for realizing communication interaction between the device and other devices, which can be realized through wired mode (for example, USB, network cable, etc.) or wireless mode (for example, mobile network, WIFI, Bluetooth, etc.).

[0185] The bus is used for transmitting information between various components (for example, the processor 400, the memory 500, the input / output interface and the communication interface) of the device.

[0186] The processor 400, the memory 500, the input / output interface and the communication interface can realize communication connection between each other in the device through the bus.

[0187] The contents in the above method embodiments are applicable to the present robot embodiment, the present robot embodiment specifically realizes the same functions as the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0188] Therefore, the present embodiment has at least one of the following technical effects:

[0189] 1. Without relying on external sensing devices such as laser radar and force sensor, the ground contact force can be accurately estimated in the absence of external sensing by only the dynamics model of the biped robot, so that the biped robot can more quickly and accurately perceive the terrain condition of the foot bottom, the biped robot can adaptively change the leg length based on the terrain condition, and the height stability of the head of the biped robot is maintained, thereby improving the control accuracy of the biped robot.

[0190] 2. The leg part of the biped robot is flexibly controlled by using the admittance control method, so that it can better adapt to complex terrain and maintain the height stability of the head. Through the admittance control, the biped robot can exhibit dynamic characteristics similar to a spring-damper system when interacting with complex terrain, which enables the biped robot to adjust its motion state on surfaces of different hardness, so that the actual leg length of the biped robot tends to the expected leg length, the biped robot better adapts to complex terrain, and the stability of the head of the biped robot under global control is improved, thereby effectively improving the control accuracy of the biped robot.

[0191] 3. The adaptive parameter mechanism is introduced, different admittance controller parameters are used for different terrains, so that the biped robot has better adaptability when facing different terrains, and the stability of the biped robot when moving is improved.

[0192] In summary, the embodiment of the present application is a head stabilization control scheme of a double-wheel-foot robot based on admittance control. A simplified floating base model of the double-wheel-foot robot is built, and the contact force between the two wheels of the double-wheel-foot robot and the ground is estimated according to the established dynamic model, so as to indirectly judge the ground state. Finally, the legs of the double-wheel-foot robot are controlled through admittance control, so that the head of the double-wheel-foot robot can better adapt to the terrain. Moreover, the adaptive parameter mechanism is introduced, which can better adapt to different terrains and has better anti-disturbance performance.

[0193] In some alternative embodiments, the functions / operations mentioned in the block diagrams can not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two blocks shown in succession can actually be executed substantially concurrently or the blocks can sometimes be executed in reverse order. Additionally, the embodiments presented and described in the flowcharts are provided by way of example only. The disclosed methods are not limited to the order of operations and logic flows presented in the figures. Alternative embodiments are contemplated in which the order of operations is changed and in which sub-operations described as part of a greater operation are executed out of order from that which is described.

[0194] Furthermore, although the present application is described in the context of functional modules, it is to be understood that one or more of the functions and / or features can be integrated in a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules, unless otherwise specified. It is also to be understood that detailed discussion of the actual implementation of each module is unnecessary to an understanding of the present application. Rather, the actual implementation is within the routine skill of engineers familiar with the attributes, functions and internal relationships of the various functional modules disclosed in the devices herein. Accordingly, the present application is not limited to purely hardware implementations, but also encompasses software implementations, including firmware, resident software, micro-code, etc. Accordingly, those skilled in the art will appreciate that the present application is able to be implemented in many manners and with many modifications, all of which are intended to be within the scope of the present application. Accordingly, although specific concepts have been illustrated and described herein, it is the intent that the application be practiced otherwise than as specifically described. The present application should only be limited by the appended claims, utilizing the entire scope of equivalents thereof.

[0195] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts of the prior art that make contributions or parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes several programs for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0196] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a list of ordered steps for implementing logical functions, which can be embodied in any computer readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can take programs from a program execution system, device or apparatus and execute them) or in conjunction with these program execution systems, devices or apparatus. For the purpose of this specification, "computer readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by program execution systems, devices or apparatus or in conjunction with these program execution systems, devices or apparatus.

[0197] More specific examples (non-exhaustive list) of computer readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optical scanning of the paper or other medium, followed by editing, interpreting or otherwise processing, if necessary, in other suitable ways, to be stored in a computer memory.

[0198] It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable

[0199] In the above description of the present specification, the description referring to the terms "one embodiment", "another embodiment" or "certain embodiments" or the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples.

[0200] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, alternatives and variations can be made thereto without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

[0201] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the described embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present application, and these equivalent modifications or substitutions are included in the scope defined by the claims of the present application.

Claims

1. An admittance control method for a bipedal robot, characterized in that, Includes the following steps: Admittance control is performed based on the initial expected leg length data and ground contact force of each leg to obtain the target expected leg length data of each leg; wherein, the ground contact force is obtained by estimating the contact force based on the target motor torque of each leg in the previous control cycle, and the ground contact force in the first control cycle is zero; The target motor torque for each leg is obtained by using the target expected leg length data, actual leg length data and other control data for each leg; Each leg is controlled according to the target motor torque of each leg; The target motor torque includes knee joint motor torque and other target motor torques; the process of using the target desired leg length data, actual leg length data, and other control data of each leg to perform torque processing to obtain the target motor torque of each leg includes: The motor torque of the knee joint of each leg is obtained by using the target expected leg length data and the actual leg length data for torque processing. Torque processing is performed using other control data of each leg to obtain other target motor torques for each leg; The step of using the target desired leg length data and actual leg length data of each leg to perform torque processing to obtain the knee joint motor torque of each leg includes: Based on the actual leg length data and the target desired leg length data of each leg, second processing information is obtained; wherein, the second processing information includes the acceleration and rate of change of the target desired leg length data and the rate of change of the actual leg length data; Based on the second processing information of each leg, the actual leg length data, and the target expected leg length data, the target output force of each leg is obtained; Based on the target output force of each leg, the motor torque of the knee joint of each leg is obtained; The target output force of the leg can be expressed as: Where ΔF represents the target output force; L′ leg，d This represents the target desired leg length data; This represents the rate of change in the target desired leg length data. L represents the acceleration of the change in the target desired leg length data. leg This represents the actual leg length data; k represents the rate of change of the actual leg length data. p and k d These are all parameters of a proportional-derivative controller.

2. The admittance control method for a bipedal robot according to claim 1, characterized in that, The admittance control based on the initial expected leg length data and ground contact force of each leg, to obtain the target expected leg length data for each leg, includes: Based on the initial expected leg length data of each leg, first processing information for each leg is obtained; wherein, the first processing information includes the acceleration and rate of change of the initial expected leg length data; Based on the first processing information of each leg and the ground contact force, combined with the preset admittance control equation, the target expected leg length data of each leg is obtained.

3. The admittance control method for a bipedal robot according to claim 1, characterized in that, The step of estimating the contact force based on the target motor torque of each leg in the previous control cycle includes: Based on the target motor torque of each leg in the previous control cycle, and combined with the generalized coordinates of the bipedal robot, the equations for the joint space acceleration of each leg with respect to the ground contact force are obtained. By applying wheel rolling constraints to each of the legs, the task space acceleration at the contact point between each leg and the ground is obtained; The ground contact force is obtained based on the equation of the joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of each leg at the contact point with the ground.

4. The admittance control method for a bipedal robot according to claim 3, characterized in that, The process of obtaining the equations for the joint space acceleration of each leg with respect to the ground contact force based on the target motor torque of each leg in the previous control cycle and the generalized coordinates of the bipedal robot includes: Based on the target motor torque of each leg in the previous control cycle, and combined with the generalized coordinates of the bi-wheeled robot, the dynamic model of the bi-wheeled robot is obtained. By inverting the mass matrix in the dynamic model, the equations for the joint space acceleration of each leg with respect to the ground contact force are obtained.

5. The admittance control method for a bipedal robot according to claim 3, characterized in that, The step of applying wheel rolling constraint processing to each of the legs to obtain the task space acceleration of each leg's contact point with the ground includes: Based on the generalized coordinates of the bipedal robot, the task space velocity of each leg at the contact point with the ground is obtained; The task space velocity at each contact point between the leg and the ground is differentiated to obtain the task space acceleration at each contact point between the leg and the ground.

6. The admittance control method for a bipedal robot according to claim 3, characterized in that, The process of obtaining the ground contact force based on the equation of the joint space acceleration of each leg with respect to the ground contact force and the task space acceleration of each leg's contact point with the ground includes: The task space acceleration at the contact point between each leg and the ground is set to zero, thus obtaining the ground rolling constraint state equation for each leg. The ground rolling constraint state equations of each leg are processed to obtain the joint space acceleration of each leg; The ground contact force is obtained based on the joint space acceleration of each leg and the equation of the joint space acceleration of each leg with respect to the ground contact force.

7. An admittance control device for a bipedal robot, characterized in that, include: An admittance controller is used to perform admittance control based on the initial expected leg length data and ground contact force of each leg to obtain the target expected leg length data of each leg; wherein, the ground contact force is obtained by estimating the contact force based on the target motor torque of each leg in the previous control cycle, and the ground contact force in the first control cycle is zero; A torque processor is used to process torque using the target desired leg length data, initial desired leg length data and other control data of each leg to obtain the target motor torque of each leg. A leg controller for independently controlling each leg according to the target motor torque of each leg; The target motor torque includes knee joint motor torque and other target motor torques; the process of using the target desired leg length data, actual leg length data, and other control data of each leg to perform torque processing to obtain the target motor torque of each leg includes: The motor torque of the knee joint of each leg is obtained by using the target expected leg length data and the actual leg length data for torque processing. Torque processing is performed using other control data of each leg to obtain other target motor torques for each leg; The step of using the target desired leg length data and actual leg length data of each leg to perform torque processing to obtain the knee joint motor torque of each leg includes: Based on the actual leg length data and the target desired leg length data of each leg, second processing information is obtained; wherein, the second processing information includes the change acceleration and rate of change of the target desired leg length data and the rate of change of the actual leg length data; Based on the second processing information of each leg, the actual leg length data, and the target expected leg length data, the target output force of each leg is obtained; Based on the target output force of each leg, the motor torque of the knee joint of each leg is obtained; The target output force of the leg can be expressed as: Where ΔF represents the target output force; L′ leg，d This represents the target desired leg length data; This represents the rate of change in the target desired leg length data. L represents the acceleration of the change in the target desired leg length data. leg This represents the actual leg length data; k represents the rate of change of the actual leg length data. p and k d These are all parameters of a proportional-derivative controller.

8. A bipedal robot, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the admittance control method for a bipedal robot as described in any one of claims 1-6.

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