Method, device and medium for determining constraint relationship data of wheel-legged robot

Abstract

The present application discloses a method, device, equipment and storage medium for determining the constraint relationship data of a wheel-legged robot, and belongs to the field of robotics. Before the wheel-legged robot is manufactured, multiple sets of energy parameters are determined through multiple state parameters of the active wheels, wheel legs and robot body of the wheel-legged robot. The multiple sets of energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states. Determining the first constraint relationship data and the second constraint relationship data based on multiple energy parameters conforms to the basic laws of physics. Through the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters, the constraint relationship data between the state parameters of the wheel-legged robot and the first torque and the second torque can be established. In this way, the constraint relationship data can be directly imported after the wheel-legged robot is manufactured, thereby improving the research and development efficiency of the wheel-legged robot.

Description

Technical Field

[0001] The present application relates to the field of robotics, and in particular to a method, apparatus, device, and storage medium for determining constraint relationship data of a wheel-legged robot. Background Art

[0002] Wheel-legged robots are currently attracting widespread attention from researchers due to their agility and flexibility in ground locomotion. Wheel-legged robots are robots whose main body is controlled by their wheel-leg structure. Controlling these robots to achieve a wider range of motions is currently a major research topic.

[0003] In related technologies, the various parameters of the wheel-legged robot are often calibrated and adjusted after the wheel-legged robot is manufactured, so that the wheel-legged robot can change its state through the cooperation of the wheel-leg structure. For example, the wheel-legged robot can be changed from an upright state to a lying state through the cooperation of the wheel-leg structure.

[0004] However, the method of calibrating and adjusting various parameters after the wheel-legged robot is manufactured will increase the research and development cycle of the wheel-legged robot and reduce the research and development speed of the legged robot. Summary of the Invention

[0005] The present invention provides a method, apparatus, device, and storage medium for determining constraint relationship data of a wheel-legged robot, which can accelerate the development of wheel-legged robots. The technical solution is as follows:

[0006] In one aspect, a method for determining constraint relationship data of a wheel-legged robot is provided, wherein the wheel-legged robot includes a driving wheel, a wheel leg, and a robot body, wherein the driving wheel and the wheel leg are connected via a first motor, and the robot body and the wheel leg are connected via a second motor, and the method includes:

[0007] Determining multiple sets of energy parameters of the wheel-legged robot based on multiple sets of target parameter state parameters of the active wheel, the wheel-legged robot, and the robot body, each set of energy parameters including potential energy and kinetic energy of the wheel-legged robot, and the multiple sets of state parameters corresponding to multiple states of the wheel-legged robot;

[0008] Based on multiple sets of energy parameters of the wheel-legged robot, determining first constraint relationship data of the first motor and second constraint relationship data of the second motor, the first constraint relationship data being used to represent a mathematical relationship between a first torque and the energy parameter of the first motor, and the second constraint relationship data being used to represent a mathematical relationship between a second torque and the energy parameter of the second motor;

[0009] Based on the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters, the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor are determined, and the constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor.

[0010] In one aspect, a device for determining constraint relationship data of a wheel-legged robot is provided. The wheel-legged robot includes a driving wheel, a wheel leg, and a robot body. The driving wheel is connected to the wheel leg via a first motor, and the robot body is connected to the wheel leg via a second motor. The device includes:

[0011] an energy parameter determination module, configured to determine multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the active wheels, the wheel legs, and the robot body, each set of energy parameters comprising potential energy and kinetic energy of the wheel-legged robot, the multiple sets of state parameters corresponding to multiple states of the wheel-legged robot;

[0012] a first constraint relationship data determination module, configured to determine first constraint relationship data of the first motor and second constraint relationship data of the second motor based on multiple sets of energy parameters of the wheel-legged robot, wherein the first constraint relationship data is used to represent a mathematical relationship between a first torque and the energy parameter of the first motor, and the second constraint relationship data is used to represent a mathematical relationship between a second torque and the energy parameter of the second motor;

[0013] A second constraint relationship data determination module is used to determine the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters. The constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor.

[0014] In a possible embodiment, the energy parameter determination module is used to determine the potential energy of the wheel-legged robot corresponding to any one of the multiple sets of state parameters based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance, the mass of the wheel leg and the mass of the robot body in the state parameters, wherein the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, the first distance is the distance between the center of mass of the wheel leg and the first connection point, and the second distance is the distance between the center of mass of the robot body and the third distance. The distance between two connection points, the third distance is the distance between the first connection point and the second connection point, the first connection point is the connection point between the wheel leg and the driving wheel, and the second connection point is the connection point between the robot body and the wheel leg; based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance and the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body and the radius of the driving wheel in the state parameters, the kinetic energy of the wheel-legged robot corresponding to the state parameters is determined, and the third rotation angle is the angle of rotation of the driving wheel.

[0015] In one possible embodiment, the energy parameter determination module is used to determine the first potential energy of the robot body based on the mass of the robot body, the third distance and the first rotation angle; determine the second potential energy of the robot body based on the mass of the robot body, the second distance, the first rotation angle and the second rotation angle; determine the potential energy of the wheel leg based on the mass of the wheel leg, the first distance and the first rotation angle; and determine the sum of the first potential energy, the second potential energy and the potential energy of the wheel leg as the potential energy of the wheel-legged robot corresponding to the state parameters.

[0016] In one possible embodiment, the energy parameter determination module is used to determine the kinetic energy of the driving wheel based on the mass of the driving wheel, the third rotation angle and the radius of the driving wheel; determine the kinetic energy of the wheel leg based on the mass of the wheel leg, the first rotation angle, the first distance, the third rotation angle and the radius of the driving wheel; determine the kinetic energy of the robot body based on the mass of the robot body, the first rotation angle, the second rotation angle, the third rotation angle, the second distance, the third distance and the radius of the driving wheel; and determine the sum of the kinetic energy of the driving wheel, the kinetic energy of the wheel leg and the kinetic energy of the robot body as the kinetic energy of the wheel-legged robot corresponding to the state parameters.

[0017] In a possible implementation, the energy parameter determination module is configured to determine the angular velocity of the driving wheel based on the third rotation angle; determine the translational velocity of the driving wheel based on the angular velocity of the driving wheel and the radius of the driving wheel; and determine the kinetic energy of the driving wheel based on the mass of the driving wheel, the angular velocity of the driving wheel, and the translational velocity of the driving wheel.

[0018] In one possible embodiment, the energy parameter determination module is used to determine the angular velocity of the wheel leg based on the first rotation angle; determine the translational velocity of the wheel leg based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the first rotation angle and the first distance; and determine the kinetic energy of the wheel leg based on the mass of the wheel leg, the angular velocity of the wheel leg and the translational velocity of the wheel leg.

[0019] In one possible embodiment, the energy parameter determination module is used to determine the angular velocity of the robot body based on the second rotation angle and the angular velocity of the wheel leg; determine the translational velocity of the robot body based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the angular velocity of the robot body, the second distance, the third distance, the first rotation angle, the second rotation angle, the second distance and the third distance; and determine the kinetic energy of the robot body based on the mass of the robot body, the angular velocity of the robot body and the translational velocity of the robot body.

[0020] In a possible embodiment, the first constraint relationship data includes first relationship data and second relationship data, and the first constraint relationship data determination module is used to establish the first relationship data between the kinetic energy of the wheel-legged robot in the energy parameters and the first torque for any set of energy parameters in the multiple sets of energy parameters, based on the kinetic energy of the wheel-legged robot in the energy parameters and the third rotation angle, where the third rotation angle is the angle of rotation of the active wheel; establish the second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy, the first rotation angle and the potential energy of the wheel-legged robot in the energy parameters, where the first rotation angle is the rotation angle of the wheel leg in the target space; establish the second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the second torque based on the kinetic energy, the second rotation angle and the potential energy of the wheel-legged robot in the energy parameters, where the second rotation angle is the rotation angle of the robot body relative to the wheel leg.

[0021] In one possible embodiment, the first constraint relationship data determination module is used to obtain the first driving wheel partial derivative of the kinetic energy of the wheel-legged robot in the energy parameters with respect to the angular velocity of the driving wheel, and the angular velocity of the driving wheel is determined based on the third rotation angle; obtain the second driving wheel partial derivative of the kinetic energy of the wheel-legged robot in the energy parameters with respect to the third rotation angle; obtain the first time partial derivative of the second driving wheel partial derivative with respect to time; and establish the first relationship data based on the first time partial derivative and the first driving wheel partial derivative.

[0022] In a possible embodiment, the first constraint relationship data determination module is used to obtain the first wheel-leg partial derivative of the kinetic energy of the wheel-leg type robot in the energy parameters with respect to the angular velocity of the wheel leg, and the angular velocity of the wheel leg is determined based on the first rotation angle; obtain the second wheel-leg partial derivative of the kinetic energy of the wheel-leg type robot in the energy parameters with respect to the first rotation angle; obtain the second time partial derivative of the second wheel-leg partial derivative with respect to time; and establish the second relationship data based on the second time partial derivative and the first wheel-leg partial derivative.

[0023] In one possible embodiment, the first constraint relationship data determination module is used to obtain a first robot body partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the angular velocity of the robot body, and the angular velocity of the robot body is determined based on the first rotation angle and the second rotation angle; obtain a second robot body partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the second rotation angle; obtain a third time partial derivative of the second robot body partial derivative with respect to time; and establish the second constraint relationship data based on the third time partial derivative and the first robot body partial derivative.

[0024] In one possible embodiment, the second constraint relationship data determination module is used to establish constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data, the value range of the state parameter, the value range of the first torque, and the value range of the second torque.

[0025] In a possible embodiment, the state parameters include a first rotation angle, a second rotation angle, a third rotation angle, the angular velocity of the driving wheel, the angular velocity of the wheel leg and the angular velocity of the robot body, the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, and the third rotation angle is the angle of rotation of the driving wheel. The second constraint relationship data determination module is used to establish, within the value range of the state parameter and the value range of the first torque, the constraint relationship data between the first torque of the first motor and the third rotation angle, the angular velocity of the driving wheel, the first rotation angle and the angular velocity of the wheel leg based on the first constraint relationship data; within the value range of the state parameter and the value range of the second torque, the constraint relationship data between the second torque of the second motor and the second rotation angle and the angular velocity of the robot body based on the second constraint relationship data.

[0026] On the one hand, a computer device is provided, which includes one or more processors and one or more memories, wherein at least one computer program is stored in the one or more memories, and the computer program is loaded and executed by the one or more processors to implement a method for determining the constraint relationship data of the wheel-legged robot.

[0027] On the one hand, a computer-readable storage medium is provided, in which at least one computer program is stored. The computer program is loaded and executed by a processor to implement a method for determining constraint relationship data of the wheel-legged robot.

[0028] On the one hand, a computer program is provided, which, when executed by a processor, implements a method for determining constraint relationship data of the wheel-legged robot.

[0029] Through the technical solutions provided in the embodiments of the present application, before the wheel-legged robot is manufactured, multiple sets of energy parameters are determined based on multiple state parameters of the active wheels, wheel legs, and robot body of the wheel-legged robot. These multiple sets of energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states. Determining the first constraint relationship data and the second constraint relationship data based on multiple energy parameters conforms to the basic laws of physics. Through the first constraint relationship data, the second constraint relationship data, and these multiple sets of state parameters, constraint relationship data between the state parameters of the wheel-legged robot and the first torque and the second torque can be established. In this way, after the wheel-legged robot is manufactured, this constraint relationship data can be directly imported, thereby improving the research and development efficiency of the wheel-legged robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0031] Figure 1 Schematic diagram of an implementation environment of a method for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application;

[0032] Figure 2 Schematic diagram of a wheel-legged robot in a two-wheel state provided by an embodiment of the present application;

[0033] Figure 3 Schematic diagram of a wheel-legged robot in a four-wheel state provided by an embodiment of the present application;

[0034] Figure 4 Schematic diagram of a wheel-legged robot provided by an embodiment of the present application transforming from a two-wheel state to a four-wheel state;

[0035] Figure 5 This is a flow chart of a method for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application;

[0036] Figure 6 This is a flow chart of a method for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application;

[0037] Figure 7 This is a simplified diagram of a wheel-legged robot provided in an embodiment of the present application;

[0038] Figure 8 This is a schematic diagram of changes in torque and state parameters provided by an embodiment of the present application;

[0039] Figure 9 This is another schematic diagram of changes in torque and state parameters provided in an embodiment of the present application;

[0040] Figure 10 This is another schematic diagram of changes in torque and state parameters provided in an embodiment of the present application;

[0041] Figure 11 This is another schematic diagram of changes in torque and state parameters provided in an embodiment of the present application;

[0042] Figure 12 This is another schematic diagram of changes in torque and state parameters provided in an embodiment of the present application;

[0043] Figure 13This is another schematic diagram of changes in torque and state parameters provided in an embodiment of the present application;

[0044] Figure 14 This is a schematic structural diagram of a device for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application;

[0045] Figure 15 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present application;

[0046] Figure 16 This is a structural diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0048] In this application, the terms "first", "second", etc. are used to distinguish identical or similar items with substantially the same effects and functions. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there any limitation on the quantity and execution order.

[0049] Artificial Intelligence (AI) refers to the theories, methods, techniques, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, to perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results. In other words, AI is a comprehensive technology within computer science that seeks to understand the essence of intelligence and produce new intelligent machines that can respond in a manner similar to human intelligence. AI also studies the design principles and implementation methods of various intelligent machines, enabling them to possess the capabilities of perception, reasoning, and decision-making.

[0050] Artificial intelligence (AI) technology is a comprehensive discipline encompassing a wide range of fields, encompassing both hardware and software technologies. Foundational AI technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0051] The solution provided in this application mainly relates to the field of robotics in artificial intelligence technology. A robot is a mechanical and electronic device that can imitate certain human skills by combining mechanical transmission and modern microelectronics technology. With the development of computer technology and artificial intelligence technology, the functions and technical levels of robots have been greatly improved. Mobile robots and robot vision and touch technologies are typical representatives.

[0052] Wheel-legged robot: A wheel-legged robot is a robot that uses a wheel-legged structure to control its motion. It has high wheel energy and strong adaptability, and can overcome uneven terrain. Among them, the wheel-legged structure consists of three parts, including driving wheels, wheel legs, and the robot body. The wheel-legged structure mentioned here is the structure formed by the cooperation between the driving wheels and the wheel legs. The robot body includes multiple components. For example, the robot body includes the robot's arms, torso, and waist. In the embodiment of this application, the structure of the robot body is set by technicians according to actual conditions, and this embodiment of the application does not limit this.

[0053] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions.

[0054] Figure 1 This is a schematic diagram of the implementation environment of a method for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application, see Figure 1 , the implementation environment may include a terminal 110 and a server 140.

[0055] Terminal 110 is connected to server 140 via a wireless network or a wired network. Optionally, terminal 110 is a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, etc., but is not limited thereto. Terminal 110 has installed and runs an application that supports determining constraint relationship data of the wheel-legged robot.

[0056] Server 140 is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. Server 140 provides background services for applications running on terminal 110.

[0057] Those skilled in the art will appreciate that the number of terminals and servers can be greater or lesser. For example, there may be only one terminal, or dozens, hundreds, or even more terminals, in which case the implementation environment may also include other terminals. The embodiments of this application do not limit the number of terminals or device types.

[0058] After introducing the implementation environment of the embodiment of the present application, the application scenario of the embodiment of the present application will be introduced in combination with the above-mentioned implementation environment. In the following description process, the terminal is the terminal 110 in the above-mentioned implementation environment, and the server is the server 140 in the above-mentioned implementation environment.

[0059] The technical solution provided by the embodiment of the present application is applied in the scenario of determining the constraint relationship data of a wheel-legged robot. When determining the constraint relationship data of the wheel-legged robot, it is not necessary to complete the wheel-legged robot. The technical solution provided by the embodiment of the present application can be executed during the process of manufacturing the wheel-legged robot or before manufacturing the wheel-legged robot. In this way, after the wheel-legged robot is manufactured, the constraint relationship data determined by the technical solution provided by the embodiment of the present application can be imported into the wheel-legged robot, thereby improving the research and development efficiency of the wheel-legged robot. The wheel-legged robot includes three parts, namely a driving wheel, a wheel leg and a robot body, wherein the driving wheel is connected to the wheel leg through a first motor, and the wheel leg is connected to the robot body through a second motor. The first motor can drive the driving wheel to rotate and can also drive the wheel leg and the driving wheel to rotate relative to each other. The second motor can drive the robot body and the wheel leg to rotate relative to each other. As described above, the structure of the robot body is set by technicians according to actual conditions, and the embodiment of the present application does not limit this. When determining the constraint relationship data, the terminal obtains multiple sets of state parameters for the wheel-legged robot's driving wheels, wheel legs, and robot body from the server. The multiple sets of state parameters correspond to various states of the wheel-legged robot, with the wheel legs having different angles in different states. Based on the multiple sets of state parameters for the wheel-legged robot's driving wheels, wheel legs, and robot body, the terminal determines multiple sets of energy parameters for the wheel-legged robot. Each set of energy parameters includes potential energy and kinetic energy of the wheel-legged robot. The multiple sets of energy parameters correspond to multiple states, meaning each set of energy parameters represents the energy parameters of the wheel-legged robot in different states. Based on the multiple sets of energy parameters for the wheel-legged robot, the terminal determines multiple first torques for the first motor and multiple second torques for the second motor. Among the multiple first torques and multiple second torques, each state of the wheel-legged robot corresponds to a first torque and a second torque, and the first torque and the second torque constitute a torque pair. The multiple torques correspond to the various states of the wheel-legged robot. Based on the multiple first torques, the multiple second torques, and the multiple sets of state parameters, the terminal determines constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first click, and the second torque of the second motor. The constraint relationship data is used to determine the first torque of the first motor and the second torque of the second motor based on the state parameters of the wheel-legged robot. After the wheel-legged robot is manufactured, the terminal imports the constraint relationship data into the wheel-legged robot. When the wheel-legged robot needs to be transformed, the first torque of the first motor and the second torque of the second motor can be determined based on the state parameters acquired in real time and the constraint relationship data, thereby completing the corresponding state transformation.

[0060] In some embodiments, the wheel-legged robot includes two active wheels and two wheel legs, and each wheel leg of the wheel-legged robot includes a passive wheel. In this case, the wheel-legged robot has two final states. The first final state is a two-wheel state, that is, the wheel-legged robot moves via the two active wheels. In the two-wheel state, the direction of the wheel legs of the wheel-legged robot is vertically upward. The second final state is a four-wheel state, that is, the wheel-legged robot moves via the two active wheels and the two passive wheels. In the four-wheel state, the direction of the wheel legs of the wheel-legged robot points from the active wheels to the passive wheels. The difference between the active wheels and the passive wheels is that the active wheels are actively rotated by the first click, and the passive wheels are passively rotated under the drive of the active wheels. In this case, the above-mentioned multiple states include multiple intermediate states when the wheel-legged robot changes from the four-wheel state to the two-wheel state, or include multiple intermediate states when the wheel-legged robot changes from the two-wheel state to the four-wheel state.

[0061] For example, see Figure 2 , shows a schematic diagram of the double-wheel state of the wheel-legged robot, Figure 2 In the figure, the wheel-legged robot 200 includes a driving wheel 201, a wheel leg 202, a passive wheel 2021 and a robot body 203. In the dual-wheel state, the wheel-legged robot 200 moves by rotating the two driving wheels 201. The direction of the wheel leg 202 is vertically upward. Of course, since the structure of the robot body 203 is set by technicians according to actual conditions, when the robot body 203 adopts different structures, the wheel leg 202 can also face different directions while maintaining balance. This embodiment of the application does not limit this. Figure 3 , which shows a schematic diagram of the four-wheel state of the wheel-legged robot. Figure 3 In the figure, the wheel-legged robot 300 includes a driving wheel 301, a wheel leg 302, a passive wheel 3021 and a robot body 303. In the four-wheel state, the wheel-legged robot 300 moves by rotating two driving wheels 301 and two passive wheels 3021.

[0062] It should be noted that the above Figure 2 and Figure 3 This is a structural diagram of a wheel-legged robot provided in an embodiment of the present application. In other possible implementations, the wheel-legged robot can also have other structures, which is not limited in this embodiment of the present application.

[0063] In the process of the wheel-legged robot switching from a two-wheeled state to a four-wheeled state, in the two-wheeled state, the two active wheels of the wheel-legged robot are in contact with the ground, and the two wheel legs of the wheel-legged robot are both vertically upward. The rotation of the two first motors on the two active wheels drives the two wheel legs to tilt. When the passive wheels on the two wheel legs are in contact with the ground, the state switching is completed, and the wheel-legged robot switches from a two-wheeled state to a four-wheeled state. In this case, the above-mentioned multiple states are also multiple intermediate states of the wheel-legged robot switching from a two-wheeled state to a four-wheeled state. For example, see Figure 4 , from left to right, shows a schematic diagram of the wheel-legged robot 400 switching from a two-wheel state to a four-wheel state. The wheel-legged robot 400 includes a driving wheel 401, a wheel leg 402, a driven wheel 4021 and a robot body 403.

[0064] During the process of the wheel-legged robot switching from the four-wheel state to the two-wheel state, in the four-wheel state, the two active wheels and the two passive wheels of the wheel-legged robot are in contact with the ground. The rotation of the two first motors on the two active wheels drives the two wheel legs to rotate upward. When the passive wheels on the two wheel legs are vertically upward, the state switching is completed, and the wheel-legged robot switches from the four-wheel state to the two-wheel state. In this case, the above-mentioned multiple states are also the multiple intermediate states of the wheel-legged robot switching from the four-wheel state to the two-wheel state. Figure 4 , the process from right to left is a schematic diagram of the wheel-legged robot switching from a four-wheel state to a two-wheel state.

[0065] After introducing the implementation environment and application scenarios of the embodiment of this application, the technical solutions provided by the embodiment of this application are introduced below. Figure 5 The method for determining the constraint relationship data of the wheel-legged robot provided in the embodiment of the present application can be executed by a terminal or a server, or can be executed jointly by the terminal and the server. In the embodiment of the present application, the execution subject is taken as an example to illustrate that the wheel-legged robot includes a driving wheel, a wheel leg and a robot body. The driving wheel is connected to the wheel leg through a first motor, and the robot body is connected to the wheel leg through a second motor. The method includes the following steps.

[0066] 501. The terminal determines multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the driving wheel, the wheel-legged robot and the robot body. Each set of energy parameters includes potential energy and kinetic energy of the wheel-legged robot. The multiple sets of state parameters correspond to multiple states of the wheel-legged robot.

[0067] The multiple sets of state parameters correspond to the various states of the wheel-legged robot. Here, the states refer to the angles of the wheel-legged robot's wheel legs, which vary in different states. For example, when the wheel-legged robot's wheel legs include passive wheels, and when the wheel-legged robot changes from a four-wheel state to a two-wheel state, the wheel-legged robot's wheel legs adjust from an initial angle to a target angle. The multiple states refer to the multiple intermediate states of the wheel legs changing from the initial angle to the target angle. If the initial angle is 10° and the target angle is 90°, the multiple states refer to the multiple intermediate states of the wheel legs changing from 10° to 90°. The state parameters of the wheel-legged robot correspond one-to-one with the states of the wheel-legged robot. The energy parameters determined by the terminal based on the state parameters also correspond one-to-one with the states of the wheel-legged robot. That is, the energy parameters correspond one-to-one with the states of the wheel-legged robot. These multiple energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states.

[0068] 502. The terminal determines the first constraint relationship data of the first motor and the second constraint relationship data of the second motor based on multiple sets of energy parameters of the wheel-legged robot, wherein the first constraint relationship data is used to represent the mathematical relationship between the first torque and the energy parameter of the first motor, and the second constraint relationship data is used to represent the mathematical relationship between the second torque and the energy parameter of the second motor.

[0069] Among them, the first torque of the first motor is the torque that controls the output of the first motor, and the second torque of the second motor is the torque that controls the output of the second motor. The first constraint relationship is used to express the mathematical relationship between the first torque and the energy parameter, that is, the mathematical relationship between the first torque and the kinetic energy and potential energy of the wheel-legged robot. The second constraint relationship is used to express the mathematical relationship between the second torque and the energy parameter, that is, the mathematical relationship between the second torque and the kinetic energy and potential energy of the wheel-legged robot. The process of determining the first constraint relationship data and the second constraint relationship data is also the process of establishing the dynamic model of the wheel-legged robot.

[0070] 503. The terminal determines the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data, and the multiple sets of state parameters. The constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor.

[0071] Among them, after establishing the constraint relationship data among the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor, during the state transformation of the wheel-legged robot, it can determine the first torque of the first motor and the second torque of the second motor based on its own state parameters and the constraint relationship data, and control the first motor to output according to the first torque, and control the second motor to output according to the second torque, thereby completing the state transformation.

[0072] Through the technical solutions provided in the embodiments of the present application, before the wheel-legged robot is manufactured, multiple sets of energy parameters are determined based on multiple state parameters of the active wheels, wheel legs, and robot body of the wheel-legged robot. These multiple sets of energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states. Determining the first constraint relationship data and the second constraint relationship data based on multiple energy parameters conforms to the basic laws of physics. Through the first constraint relationship data, the second constraint relationship data, and these multiple sets of state parameters, constraint relationship data between the state parameters of the wheel-legged robot and the first torque and the second torque can be established. In this way, after the wheel-legged robot is manufactured, this constraint relationship data can be directly imported, thereby improving the research and development efficiency of the wheel-legged robot.

[0073] It should be noted that the above steps 501-503 are a brief introduction to the technical solution provided in the embodiment of the present application. The following will illustrate the method for determining the constraint relationship data of the wheel-legged robot provided in the embodiment of the present application with reference to some examples. The wheel-legged robot includes a driving wheel, a wheel leg, and a robot body. The driving wheel is connected to the wheel leg through a first motor, and the robot body is connected to the wheel leg through a second motor. Figure 6 , the method includes the following steps.

[0074] 601. The terminal obtains multiple groups of status parameters of the driving wheel, the wheel leg, and the robot body in the wheel-legged robot.

[0075] In this wheel-legged robot, a driving wheel is connected to the wheel leg via a first motor. Driving the first motor controls relative rotation between the wheel leg and the driving wheel. The wheel leg is connected to the robot body via a second motor. Driving the second motor controls relative rotation between the robot body and the wheel leg. In some embodiments, the wheel-legged robot includes two driving wheels, two wheel legs, and a robot body. The two driving wheels are connected to the two wheel legs via two first motors, respectively, and the two wheel legs are connected to two sides of the robot body via two second motors. When controlling the state transition of the wheel-legged robot, the two first motors and the two second motors are simultaneously driven. For example, when the wheel-legged robot's wheel legs include passive wheels, when the wheel-legged robot transitions from a four-wheel state to a two-wheel state, the two first motors drive the two wheel legs to rotate upward, and driven by the two wheel legs, the robot body also moves upward. During the upward movement of the robot body, the two second motors adjust the relative angle between the robot body and the two wheel legs, thereby enabling the wheel-legged robot to maintain balance during the state transition. In some embodiments, the robot body includes multiple components, such as the waist and upper limbs of the robot, wherein the upper limbs include single-arm, double-arm or more robotic arms. The embodiments of the present application do not limit the number and degree of freedom of the robotic arms. During the state transformation of the wheel-legged robot, the various components of the robot body remain relatively stationary, that is, the connecting joints between the various components of the robot body remain locked. In this case, the robot body can be regarded as a rigid body. Since the wheel-legged robot has a symmetrical structure, in the subsequent description, half of the wheel-legged robot, that is, a driving wheel, a wheel leg and half of the robot body, will be used as an example for description. The half robot body is also the following robot body. See. Figure 7 The structure of the wheel-legged robot is abstracted into a second-order inverted pendulum model in a plane. Figure 7 In the figure, the wheel-legged robot includes an active wheel 701, wheel legs 702 and a robot body 703.

[0076] For any one of the multiple sets of state parameters, including the state parameters of the driving wheel, the state parameters of the wheel legs, and the state parameters of the robot body, the set of state parameters corresponds to one of the multiple states. The state here refers to the angle of the wheel legs of the wheel-legged robot. The angle of the wheel legs of the wheel-legged robot is different in different states. A set of state parameters is used to represent the state of the wheel-legged robot at a certain moment. For example, the state parameters of the driving wheel in the set of state parameters include the angle of rotation of the driving wheel, the state parameters of the wheel legs in the set of state parameters include the rotation angle of the wheel legs, and the state parameters of the robot body include the rotation angle of the robot body, etc. In the case where the state transformation refers to the wheel-legged robot changing from a four-wheel state to a two-wheel state, the multiple states are multiple intermediate states from the four-wheel state to the two-wheel state, and multiple sets of state parameters are used to represent the multiple intermediate states.

[0077] In one possible implementation, the terminal obtains multiple sets of state parameters for the active wheel, the wheel legs, and the robot body of the wheel-legged robot from a server. In this case, these multiple sets of state parameters are obtained by the server simulating the wheel-legged robot's transitions between multiple states based on the robot's structure. In this implementation, multiple sets of state parameters can be obtained by simulating the robot's state transitions in advance through the server, without having to wait for the robot to be manufactured, resulting in increased efficiency.

[0078] For example, a terminal sends a state parameter acquisition request to a server, the state parameter acquisition request carrying the identifier of the wheel-legged robot. The server receives the state parameter acquisition request and obtains the identifier of the wheel-legged robot from the state parameter acquisition request. The server performs a query based on the identifier of the wheel-legged robot to obtain multiple sets of state parameters for the active wheel, the wheel leg, and the robot body of the wheel-legged robot. The server sends these multiple sets of state parameters to the terminal, which then obtains these multiple sets of state parameters.

[0079] In some embodiments, if the server does not store the multiple sets of state parameters for the wheel-legged robot, the state parameter acquisition request also carries the wheel-legged robot's attributes, initial state, and target state. The wheel-legged robot's attributes include the number of components, component types, component dimensions, component mass, and the connectivity between components. The initial state refers to the starting point of the wheel-legged robot's state during the simulation, such as the four-wheel state described above; the target state refers to the ending point of the wheel-legged robot's state during the simulation, such as the two-wheel state described above. In some embodiments, the initial state and target state are described using two sets of state parameters, respectively. After receiving the state parameter acquisition request, the server can obtain the wheel-legged robot's attributes, initial state, and target state from the state parameter acquisition request. Based on the wheel-legged robot's attributes, initial state, and target state, the server simulates the process of the wheel-legged robot transforming from the initial state to the target state, obtaining the multiple sets of state parameters. The server sends these multiple sets of state parameters to the terminal, which then acquires them. In some embodiments, the state parameter acquisition request also carries the upper limit and lower limit of the state parameter, so that the server can be more accurate in determining the multiple groups of state parameters.

[0080] In one possible implementation, a terminal performs a query based on the wheel-legged robot's identifier to obtain multiple sets of state parameters for the active wheel, the wheel leg, and the robot body. In this case, the terminal is the one used to design the wheel-legged robot, and the terminal stores the multiple sets of state parameters for the wheel-legged robot. These multiple sets of state parameters are obtained by simulating the wheel-legged robot's transitions between multiple states based on its structure.

[0081] In some embodiments, the timing for the wheel-legged robot to switch states is set by technicians based on actual conditions. For example, the wheel-legged robot includes an environmental sensor. When a specified environment is detected by the environmental sensor, the wheel-legged robot can change states. The embodiments of the present application do not limit the timing for the wheel-legged robot to change states.

[0082] 602. The terminal determines multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the driving wheel, the wheel-legged robot and the robot body, each set of the energy parameters includes the potential energy and kinetic energy of the wheel-legged robot, and the multiple sets of state parameters correspond to multiple states of the wheel-legged robot.

[0083] Among them, the state parameters of the wheel-legged robot correspond one-to-one to the state of the wheel-legged robot, and the energy parameters determined by the terminal based on the state parameters also correspond one-to-one, that is, the energy parameters correspond one-to-one to the state of the wheel-legged robot. Multiple energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states.

[0084] In a possible embodiment, for any set of state parameters in the multiple sets of state parameters, the terminal determines the potential energy of the wheel-legged robot corresponding to the state parameter based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance, the mass of the wheel leg and the mass of the robot body in the state parameter, the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, the first distance is the distance between the center of mass of the wheel leg and the first connection point, the second distance is the distance between the center of mass of the robot body and the second connection point, the third distance is the distance between the first connection point and the second connection point, the first connection point is the connection point between the wheel leg and the driving wheel, and the second connection point is the connection point between the robot body and the wheel leg. The terminal determines the kinetic energy of the wheel-legged robot corresponding to the state parameters based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance, the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body and the radius of the driving wheel in the state parameters, where the third rotation angle is the angle of rotation of the driving wheel.

[0085] For ease of understanding, the following Figure 7 The above parameters are explained. Figure 7The first rotation angle θ1 is the rotation angle of the wheel leg 702 within the target space, which is the space in which the wheel-legged robot resides. The angle of rotation of the wheel leg 702 within the target space is also called the rotation angle in the world coordinate system. The second rotation angle θ2 is the rotation angle of the robot body 703 relative to the wheel leg 702. The second rotation angle θ2 is different from the first rotation angle θ1. The second rotation angle θ2 is not a rotation angle within the target space, but a rotation angle in the space constructed with the wheel leg 702 as the reference system. The first distance is the distance between the center of mass m1 of the wheel leg 702 and the first connection point p1. The first connection point p1 is the connection point between the wheel leg 702 and the driving wheel 701, that is, the location where the wheel leg 702 is connected to the driving wheel 701 via the first motor. The location of the center of mass of the wheel leg 702 is determined by the terminal based on the mass distribution of the wheel leg 702. If the wheel leg 702 is a regular and uniform object, the center of mass of the wheel leg 702 is the geometric center of the wheel leg 702. The second distance is the distance between the mass center m2 of the robot body 703 and the second connection point p2. The second connection point p2 is the connection point between the robot body 703 and the wheel leg 702, that is, the position where the robot body 703 is connected to the wheel leg 702 through the second motor. The third distance is the distance between the first connection point p1 and the second connection point p2. The mass of the wheel leg 702 and the mass of the robot body 703 have been determined in the design stage. The mass of the wheel leg 702 and the mass of the robot body 703 have been input by the technician on the terminal. The third rotation angle is the rotation angle of the driving wheel.

[0086] During a state transition, the components of the wheel-legged robot's main body do not move relative to each other. The robot body can be considered a rigid body, and the positions of the robot's center of mass and the wheel-leg's center of mass do not change. Furthermore, the positions of the first connection point between the wheel-leg and the driving wheel, and the second connection point between the wheel-leg and the robot body, do not change.

[0087] In some embodiments, the potential energy of the wheel-legged robot determined in the above embodiments is the gravitational potential energy of the wheel-legged robot, and the zero potential energy surface of the gravitational potential energy is the plane where the center of mass of the driving wheel is located.

[0088] In order to explain the above embodiment more clearly, the following will be divided into two parts to explain the above embodiment.

[0089] The first part, the terminal determines the potential energy of the wheel-legged robot corresponding to the state parameter based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance, the mass of the wheel leg and the mass of the robot body in the state parameter.

[0090] In one possible implementation, the terminal determines a first potential energy of the robot body based on the mass of the robot body, the third distance, and the first rotation angle. The terminal determines a second potential energy of the robot body based on the mass of the robot body, the second distance, the first rotation angle, and the second rotation angle. The terminal determines a potential energy of the wheel leg based on the mass of the wheel leg, the first distance, and the first rotation angle. The terminal determines the sum of the first potential energy, the second potential energy, and the potential energy of the wheel leg as the potential energy of the wheel-legged robot corresponding to the state parameter.

[0091] For example, the terminal determines the potential energy of the wheel-legged robot corresponding to the state parameter through the following formula (1).

[0092] V=M2gl0cos(θ1)+M2gl2cos(θ2-θ1)+M1gl1cos(θ1) (1)

[0093] Among them, V is the potential energy of the wheel-leg robot, M2 is the mass of the robot body, M1 is the mass of the wheel leg, l0 is the third distance, l2 is the second distance, l1 is the first distance, g is the acceleration of gravity, θ2 is the second rotation angle, θ1 is the first rotation angle, M2gl0cos(θ1) is the first potential energy, M2gl2cos(θ2-θ1) is the second potential energy, and M1gl1cos(θ1) is the potential energy of the wheel leg.

[0094] In the second part, the terminal determines the kinetic energy of the wheel-legged robot corresponding to the state parameters based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance, the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body and the radius of the driving wheel in the state parameters.

[0095] In one possible implementation, the terminal determines the kinetic energy of the driving wheel based on the mass of the driving wheel, the third rotation angle, and the radius of the driving wheel. The kinetic energy of the wheel leg is determined based on the mass of the wheel leg, the first rotation angle, the first distance, the third rotation angle, and the radius of the driving wheel. The terminal determines the kinetic energy of the robot body based on the mass of the robot body, the first rotation angle, the second rotation angle, the third rotation angle, the second distance, the third distance, and the radius of the driving wheel. The terminal determines the sum of the kinetic energy of the driving wheel, the kinetic energy of the wheel leg, and the kinetic energy of the robot body as the kinetic energy of the wheel-legged robot corresponding to the state parameter.

[0096] For example, the terminal determines the angular velocity of the driving wheel based on the third rotation angle. In some embodiments, the angular velocity of the driving wheel is obtained by taking the derivative of the third rotation angle with respect to time. The terminal determines the translational velocity of the driving wheel based on the angular velocity of the driving wheel and the radius of the driving wheel. In some embodiments, the translational velocity of the driving wheel is the product of the angular velocity of the driving wheel and the radius of the driving wheel. The terminal determines the kinetic energy of the driving wheel based on the mass of the driving wheel, the angular velocity of the driving wheel, and the translational velocity of the driving wheel. In some embodiments, the kinetic energy of the driving wheel includes the rotational kinetic energy and translational kinetic energy of the driving wheel. The terminal determines the angular velocity of the wheel leg based on the first rotation angle. In some embodiments, the angular velocity of the wheel leg is obtained by taking the derivative of the first rotation angle with respect to time. The terminal determines the translational velocity of the wheel leg based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the first rotation angle, and the first distance. The terminal determines the kinetic energy of the wheel leg based on the mass of the wheel leg, the angular velocity of the wheel leg, and the translational velocity of the wheel leg. In some embodiments, the kinetic energy of the wheel leg includes the rotational kinetic energy and translational kinetic energy of the wheel leg. The terminal determines the angular velocity of the robot body based on the second rotation angle and the angular velocity of the wheel leg. In some embodiments, the angular velocity of the robot body is the difference between the angular velocity obtained by taking the derivative of the second rotation angle with respect to time and the angular velocity of the wheel leg. The terminal determines the translational velocity of the robot body based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the angular velocity of the robot body, the second distance, the third distance, the first rotation angle, the second rotation angle, the second distance, and the third distance. The terminal determines the kinetic energy of the robot body based on the mass of the robot body, the angular velocity of the robot body, and the translational velocity of the robot body. In some embodiments, the kinetic energy of the robot body includes the rotational kinetic energy and translational kinetic energy of the robot body. The terminal determines the sum of the kinetic energy of the driving wheel, the kinetic energy of the wheel leg and the kinetic energy of the robot body as the kinetic energy of the wheel-legged robot corresponding to the state parameter.

[0097] For example, the terminal determines the angular velocity of the driving wheel using the following formula (2). The terminal determines the translational velocity of the driving wheel using the following formula (3). The terminal determines the kinetic energy of the driving wheel using the following formula (4).

[0098]

[0099]

[0100]

[0101] Among them, ω wheel is the angular velocity of the driving wheel, φ is the third rotation angle, is the time derivative of the third rotation angle, υ wheel is the translational speed of the driving wheel, R is the radius of the driving wheel, is the kinetic energy of the driving wheel, m is the mass of the driving wheel, and J0 is the moment of inertia of the driving wheel.

[0102] The terminal determines the angular velocity of the wheel leg using the following formula (5). The terminal determines the translational velocity of the wheel leg using the following formula (6). The terminal determines the kinetic energy of the wheel leg using the following formula (7).

[0103]

[0104]

[0105]

[0106] Among them, ω ll is the angular velocity of the wheel leg, θ1 is the first rotation angle, is the time derivative of the first rotation angle, υ ll is the translational velocity of the wheel leg, is the derivative of the third rotation angle with respect to time, l1 is the first distance, R is the radius of the wheel leg, is the kinetic energy of the wheel leg, M1 is the mass of the wheel leg, and J1 is the moment of inertia of the wheel leg.

[0107] The terminal determines the angular velocity of the robot body by the following formula (8). The terminal determines the translational velocity of the robot body by the following formula (9). The terminal determines the kinetic energy of the robot body by the following formula (10).

[0108]

[0109]

[0110]

[0111] Among them, ω Body is the angular velocity of the robot body, θ2 is the second rotation angle, is the time derivative of the second rotation angle, υ Body is the translational velocity of the robot body, is the derivative of the third rotation angle with respect to time, l2 is the second distance, l0 is the third distance, R is the radius of the driving wheel, is the kinetic energy of the robot body, M2 is the mass of the robot body, and J2 is the moment of inertia of the robot body.

[0112] In some embodiments, the terminal combines and simplifies the formula (9) to obtain the following formula (11). When the kinetic energy of the robot body is determined based on the following formula (11), the amount of calculation is smaller and the efficiency is higher.

[0113]

[0114] The terminal determines the kinetic energy of the wheel-legged robot through the following formula (12).

[0115]

[0116] in, is the kinetic energy of the wheel-legged robot.

[0117] It should be noted that the above description is based on an example of a terminal determining the energy parameter corresponding to a set of state parameters based on the state parameters. The method of the terminal determining the energy parameter based on the state parameters of other groups in the multiple groups of state parameters belongs to the same inventive concept as the above description, and the implementation process will not be repeated.

[0118] 603. The terminal determines the first constraint relationship data of the first motor and the second constraint relationship data of the second motor based on multiple sets of energy parameters of the wheel-legged robot, wherein the first constraint relationship data is used to represent the mathematical relationship between the first torque and the energy parameter of the first motor, and the second constraint relationship data is used to represent the mathematical relationship between the second torque and the energy parameter of the second motor.

[0119] Among them, the first torque of the first motor is the torque that controls the output of the first motor, and the second torque of the second motor is the torque that controls the output of the second motor. The first constraint relationship is used to express the mathematical relationship between the first torque and the energy parameter, that is, the mathematical relationship between the first torque and the kinetic energy and potential energy of the wheel-legged robot. The second constraint relationship is used to express the mathematical relationship between the second torque and the energy parameter, that is, the mathematical relationship between the second torque and the kinetic energy and potential energy of the wheel-legged robot. The process of determining the first constraint relationship data and the second constraint relationship data is also the process of establishing the dynamic model of the wheel-legged robot.

[0120] In one possible embodiment, the first constraint relationship data includes first relationship data and second relationship data. For any set of energy parameters from the multiple sets of energy parameters, the terminal establishes first relationship data between the kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters and a third rotation angle, where the third rotation angle is the angle of rotation of the driving wheel. The terminal establishes second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters, the first rotation angle, and the potential energy of the wheel-legged robot in the energy parameters. The first rotation angle is the rotation angle of the wheel-legged robot in the target space. The terminal establishes second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the second torque based on the kinetic energy of the wheel-legged robot in the energy parameters, the second rotation angle, and the potential energy of the wheel-legged robot in the energy parameters. The second rotation angle is the rotation angle of the robot body relative to the wheel-legged robot.

[0121] The meanings of the first rotation angle and the second rotation angle are as given in step 602. Figure 7 The description will not be repeated here.

[0122] In order to explain the above embodiment more clearly, the following will be divided into three parts to explain the above embodiment.

[0123] In the first part, the terminal establishes first relationship data between the kinetic energy of the wheel-legged robot in the energy parameter and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameter and the third rotation angle.

[0124] In one possible implementation, the terminal obtains a first driving wheel partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the angular velocity of the driving wheel, where the angular velocity of the driving wheel is determined based on the third rotation angle. The terminal obtains a second driving wheel partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the third rotation angle. The terminal obtains a first time partial derivative of the second driving wheel partial derivative with respect to time. The terminal establishes the first relationship data based on the first time partial derivative and the first driving wheel partial derivative.

[0125] Among them, the first driving wheel partial derivative is used to represent the changing rate of the kinetic energy of the wheel-legged robot in the angular velocity direction of the driving wheel, and the second driving wheel partial derivative is used to represent the changing rate of the kinetic energy of the wheel-legged robot in the direction of the third rotation angle.

[0126] For example, the terminal determines the first active wheel partial derivative by the following formula (13), determines the second active wheel partial derivative by the following formula (14), obtains the first time partial derivative by the following formula (15), and the form of the first relationship data is shown in the following formula (16).

[0127]

[0128]

[0129]

[0130]

[0131] Where E is the kinetic energy in the above formula (12), is the time derivative of the angular velocity of the driving wheel, is the time derivative of the angular velocity of the wheel leg, is the time derivative of the robot's angular velocity, u1 is the first torque, is the partial derivative of the first driving wheel, is the partial derivative of the second driving wheel, is the first time partial derivative. The first relational data shown in formula (16) is the result obtained by substituting the above formula (13) and formula (15) into the Euler-Lagrange equation.

[0132] In the second part, the terminal establishes second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameter and the first torque based on the kinetic energy, the first rotation angle and the potential energy of the wheel-legged robot in the energy parameter.

[0133] In one possible implementation, the terminal obtains a first wheel-leg partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the angular velocity of the wheel-legged robot, where the angular velocity of the wheel-legged robot is determined based on the first rotation angle. The terminal obtains a second wheel-leg partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the first rotation angle. The terminal obtains a second time partial derivative of the second wheel-leg partial derivative with respect to time. The terminal establishes the second relationship data based on the second time partial derivative and the first wheel-leg partial derivative.

[0134] Among them, the first wheel-leg partial derivative is used to represent the changing rate of the kinetic energy of the wheel-leg robot in the angular velocity direction of the wheel leg, and the second wheel-leg partial derivative is used to represent the changing rate of the kinetic energy of the wheel-leg robot in the direction of the third rotation angle.

[0135] For example, the terminal determines the first-round leg partial derivative by the following formula (17), determines the second-round leg partial derivative by the following formula (18), obtains the second time partial derivative by the following formula (19), and the form of the second relationship data is shown in the following formula (20).

[0136]

[0137]

[0138]

[0139]

[0140] Among them, u1 is the first moment, is the partial derivative of the first leg, is the partial derivative of the second leg, is the second time partial derivative, V is the potential energy of the wheel-legged robot, and the determination method refers to the description of formula (1) in the above step 602. The second relationship data shown in formula (20) is the result obtained by substituting the above formulas (17) and (19) into the Euler-Lagrange equation.

[0141] The third part, the terminal establishes the second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameter and the second torque based on the kinetic energy, the second rotation angle and the potential energy of the wheel-legged robot in the energy parameter.

[0142] In one possible implementation, the terminal obtains a first robot-body partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to an angular velocity of the robot body, where the angular velocity of the robot body is determined based on the first rotation angle and the second rotation angle. The terminal obtains a second robot-body partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the second rotation angle. The terminal obtains a third time partial derivative of the second robot-body partial derivative with respect to time. The terminal establishes the second constraint relationship data based on the third time partial derivative and the first robot-body partial derivative.

[0143] Among them, the first robot body partial derivative is used to represent the changing rate of the kinetic energy of the wheel-legged robot in the angular velocity direction of the robot body, and the second robot body partial derivative is used to represent the changing rate of the kinetic energy of the wheel-legged robot in the direction of the third rotation angle.

[0144] For example, the terminal determines the partial derivative of the first robot body through the following formula (21), determines the partial derivative of the second robot body through the following formula (22), obtains the third time partial derivative through the following formula (23), and the form of the second constraint relationship data is shown in the following formula (24).

[0145]

[0146]

[0147]

[0148]

[0149] Among them, u2 is the second moment, is the partial derivative of the first robot body, is the partial derivative of the second robot body, is the third time partial derivative, V is the potential energy of the wheel-legged robot, and the second relational data shown in formula (24) is the result obtained by substituting the above formulas (21) and (23) into the Euler-Lagrange equation.

[0150] Among them, the process of determining the first constraint relationship data and the second constraint relationship data through the above three parts is the process of establishing the dynamic model of the wheel-legged robot. It represents the process in which the state parameters of the wheel-legged robot change with the input torque. The first constraint relationship data and the second constraint relationship data will be used as a constraint condition for optimization in the future. The torque in the whole process is not calculated by the first constraint relationship data and the second constraint relationship data, but the torque obtained by the optimization process, which just satisfies the first constraint relationship data and the second constraint relationship data, that is, satisfies the dynamic characteristics of the wheel-legged robot.

[0151] In one possible implementation, the terminal optimizes the first constraint relationship data and the second constraint relationship data to obtain the first torque and the second torque. When the terminal simulates the state transition process of the wheel-legged robot, the simulation is performed by solving differential equations corresponding to the first torque and the second torque.

[0152] In the simulation process, using the PID (Proportion Integration Differentiation) controller without limiting the motor torque and the constraints between the components of the wheel-legged robot, the Figure 8 The results shown. Figure 8In the figure, the parameters of the PID controller are selected by technicians. State-x1 is the third rotation angle, that is, the angle of rotation of the driving wheel 801. State-x2 is the angular velocity of the driving wheel 801. State-x3 is the first rotation angle, that is, the angle of rotation of the wheel leg 802. In some embodiments, the angle of rotation of the wheel leg 802 is expressed by the angle between the wheel leg 802 and the vertical direction. State-x5 is the second rotation angle, that is, the angle of rotation of the robot body 803 relative to the wheel leg 802. State-x6 is the angular velocity of the robot body 803. u1 is the torque of the first motor, and u2 is the torque of the second motor. By Figure 8 It can be seen that the wheel-legged robot 800, driven by the first motor and the second motor, can restore balance from a certain initial angle (such as 10°), and the dynamic system characteristics meet the basic requirements.

[0153] However, in Figure 8 Under the corresponding PID controller parameters, the torque of the second motor reaches -2000Nm and 1000Nm. It is difficult for the motor to achieve such instantaneous torque. Therefore, the terminal can also optimize the parameters of the PID controller through the following step 604.

[0154] 604. The terminal determines the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data, and the multiple sets of state parameters. The constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor.

[0155] In one possible embodiment, the terminal establishes constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data, the value range of the state parameter, the value range of the first torque, and the value range of the second torque.

[0156] In some embodiments, the constraint relationship is used to control the wheel-legged robot to perform state transition.

[0157] Among them, the state parameters include a first rotation angle, a second rotation angle, a third rotation angle, the angular velocity of the driving wheel, the angular velocity of the wheel leg and the angular velocity of the robot body. The first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, and the third rotation angle is the angle of rotation of the driving wheel.

[0158] For example, the terminal establishes the constraint relationship data between the first torque of the first motor and the third rotation angle, the angular velocity of the driving wheel, the first rotation angle and the angular velocity of the wheel leg based on the first constraint relationship data within the value range of the state parameter and the value range of the first torque. The terminal establishes the constraint relationship data between the second torque of the second motor and the second rotation angle and the angular velocity of the robot body based on the second constraint relationship data within the value range of the state parameter and the value range of the second torque.

[0159] 605. The terminal optimizes the constraint relationship data to obtain target constraint relationship data among the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor.

[0160] In some embodiments, the terminal optimizes the multiple first torques and the multiple groups of state parameters within the value range of the state parameter and the value range of the first torque, and optimizes the multiple second torques and the multiple groups of state parameters within the value range of the state parameter and the value range of the second torque. The purpose of the optimization is to make the equivalent center of mass of the wheel-legged robot as close as possible to the vertical line of the wheel center of the driving wheel, so as to ensure that the wheel-legged robot always maintains balance during the state transformation process, wherein the equivalent center of mass of the wheel-legged robot is the center of mass of the wheel-legged robot regarded as a whole, and the center of mass of the whole may not exist on the wheel-legged robot.

[0161] In some embodiments, the terminal imports the value range of the state parameter, the value range of the first torque, the value range of the second torque, and the multiple sets of state parameters into GPOPS (General Purpose Optimal Control Software), and optimizes them using GPOPS to obtain the first relationship data and the second relationship data. Table 1 shows the value range of the state parameter.

[0162] Table 1

[0163]

[0164]

[0165] Among them, x1 is the third rotation angle, that is, the rotation angle of the driving wheel, x2 is the angular velocity of the driving wheel, x3 is the first rotation angle, that is, the angle of rotation of the wheel leg, x4 is the angular velocity of rotation of the wheel leg, x5 is the second rotation angle, that is, the angle of rotation of the robot body, and x6 is the angular velocity of rotation of the robot body.

[0166] An example of the value range of the first moment u1 and the second moment u2 is shown in the following formula (25).

[0167]

[0168] It should be noted that the above formula (25) is an example of the torque value range. The value range of the motor torque is determined by the motor properties. When different types of motors are used, the value range may be different.

[0169] During the experiment, a set of PID controller parameters were obtained. The form of the parameters can be found in the following formula (26).

[0170]

[0171] Among them, u1 is the first moment and u2 is the second moment.

[0172] In some embodiments, during the process of the terminal acquiring the constraint relationship data, it can also perform optimization using a consumption function as a constraint, where the consumption function is used to reduce the energy consumption of the wheel-legged robot during state transition.

[0173] The physical meaning of the consumption function is that the torque of the two motors is minimized between the initial and final moments. The initial moment is the start of the state transition for the wheel-legged robot, and the final moment is the end of the state transition. The consumption function is similar to the reward in reinforcement learning and is the objective function in the optimization process. The torque at which the consumption function reaches its minimum value is used as the target torque for the motor, and the wheel-legged robot is controlled by this target torque.

[0174] The following formula (27) shows an example of the consumption function.

[0175]

[0176] Among them, C is the consumption function, 0 is the initial time, t f is the final moment, a and b are the weights corresponding to the first motor and the second motor respectively, which are set by technicians according to actual conditions. In some embodiments, a=31, b=1.

[0177] In some embodiments, the terminal optimizes the first constraint relationship data and the second constraint relationship data based on the symbolic operation toolbox of Matlab (Matrix & Laboratory) software to obtain the first torque and the second torque. In some embodiments, the terminal can verify the differential equations corresponding to the first torque and the second torque through the ode45 function provided in Matlab, that is, the dynamic model of the wheel-legged robot is simulated by the differential equations corresponding to the first torque and the second torque, and the input sequence of the first torque and the second torque is applied to the wheel-legged robot to determine how the state of the wheel-legged robot changes within a period of time. This process, in order to calculate the dynamic response of the wheel-legged robot, is achieved by applying ode45 in Matlab to solve the differential equations corresponding to the first torque and the second torque representing the dynamic characteristics of the system.

[0178] In some embodiments, in the above description process, the differential equations of the first moment and the second moment are solved by ode45 to obtain multiple first moments and multiple second moments. The schematic diagram of simulating the state transformation process of the wheel-legged robot by loading multiple first moments and multiple second moments is shown in FIG. Figures 9-13 .

[0179] Taking the state transformation of the wheel-legged robot from four-wheel state to two-wheel state as an example, Figure 9 - Figure 13 In the figure, the upper left figure is a schematic diagram of a simplified model of the wheel-legged robot 900 on a two-dimensional plane, and the upper right two figures are the torque-frequency curves of the wheel motor (first motor) and the hip joint motor (second motor). It can be seen that the torque of the two motors in the entire motion trajectory meets the requirements, and the speed at each moment is also below the required speed. The five figures from left to right in the lower half of the figure are curves of the angular velocity x2 of the driving wheel, the first rotation angle x3, the second rotation angle x5, the first torque u1 and the second torque u2 changing with time. Figure 9 - Figure 13 From the control effect of the wheel-legged robot shown, it can be seen that the wheel-legged robot can successfully switch from the four-wheel state to the two-wheel state, and maintain the two-wheel balance and stability without falling.

[0180] All of the above optional technical solutions can be combined in any way to form optional embodiments of the present application, and will not be described in detail here.

[0181] Through the technical solutions provided in the embodiments of the present application, before the wheel-legged robot is manufactured, multiple sets of energy parameters are determined based on multiple state parameters of the active wheels, wheel legs, and robot body of the wheel-legged robot. These multiple sets of energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states. Determining the first constraint relationship data and the second constraint relationship data based on multiple energy parameters conforms to the basic laws of physics. Through the first constraint relationship data, the second constraint relationship data, and these multiple sets of state parameters, constraint relationship data between the state parameters of the wheel-legged robot and the first torque and the second torque can be established. In this way, after the wheel-legged robot is manufactured, this constraint relationship data can be directly imported, thereby improving the research and development efficiency of the wheel-legged robot.

[0182] In the embodiments of the present application, a complete theoretical system of modeling, planning, and control is applied, taking into account the state parameters and dynamic characteristics of a simplified model of a wheel-legged robot. By predicting the state changes of the wheel-legged robot and adaptively designing control inputs, it is possible to ensure that the performance of the motor is always controlled within the actual torque-frequency curve and physical limits. Introducing the technical solutions provided by the embodiments of the present application during the design phase of the wheel-legged robot allows the performance of the wheel-legged robot to be evaluated during the simulation phase, which to a certain extent assists in the design process such as motor selection and speed reducer ratio configuration. There is no need to wait until the wheel-legged robot is assembled before testing, which can greatly shorten the development iteration cycle of the wheel-legged robot.

[0183] Figure 14 This is a schematic diagram of a device for determining constraint relationship data of a wheel-legged robot provided in an embodiment of the present application. The wheel-legged robot includes a driving wheel, a wheel leg, and a robot body. The driving wheel is connected to the wheel leg via a first motor, and the robot body is connected to the wheel leg via a second motor. Figure 14 The device includes: an energy parameter determination module 1401, a first constraint relationship data determination module 1402 and a second constraint relationship data determination module 1403.

[0184] The energy parameter determination module 1401 is used to determine multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the driving wheel, the wheel leg and the robot body. Each set of energy parameters includes the potential energy and kinetic energy of the wheel-legged robot. The multiple sets of state parameters correspond to multiple states of the wheel-legged robot.

[0185] The first constraint relationship data determination module 1402 is used to determine the first constraint relationship data of the first motor and the second constraint relationship data of the second motor based on multiple sets of energy parameters of the wheel-legged robot. The first constraint relationship data is used to represent the mathematical relationship between the first torque and the energy parameter of the first motor, and the second constraint relationship data is used to represent the mathematical relationship between the second torque and the energy parameter of the second motor.

[0186] The second constraint relationship data determination module 1403 is used to determine the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters. The constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor.

[0187] In a possible embodiment, the energy parameter determination module 1401 is used to determine the potential energy of the wheel-legged robot corresponding to any set of state parameters in the multiple sets of state parameters based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance in the state parameters, the mass of the wheel leg, and the mass of the robot body, wherein the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, the first distance is the distance between the center of mass of the wheel leg and the first connection point, the second distance is the distance between the center of mass of the robot body and the second connection point, the third distance is the distance between the first connection point and the second connection point, the first connection point is the connection point between the wheel leg and the driving wheel, and the second connection point is the connection point between the robot body and the wheel leg. Based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance, the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body and the radius of the driving wheel in the state parameters, the kinetic energy of the wheel-legged robot corresponding to the state parameters is determined, and the third rotation angle is the angle of rotation of the driving wheel.

[0188] In one possible implementation, the energy parameter determination module 1401 is configured to determine a first potential energy of the robot body based on the mass of the robot body, the third distance, and the first rotation angle. Determine a second potential energy of the robot body based on the mass of the robot body, the second distance, the first rotation angle, and the second rotation angle. Determine the potential energy of the wheel leg based on the mass of the wheel leg, the first distance, and the first rotation angle. The sum of the first potential energy, the second potential energy, and the potential energy of the wheel leg is determined as the potential energy of the wheel-legged robot corresponding to the state parameter.

[0189] In one possible implementation, the energy parameter determination module 1401 is configured to determine the kinetic energy of the driving wheel based on the mass of the driving wheel, the third rotation angle, and the radius of the driving wheel. The kinetic energy of the wheel leg is determined based on the mass of the wheel leg, the first rotation angle, the first distance, the third rotation angle, and the radius of the driving wheel. The kinetic energy of the robot body is determined based on the mass of the robot body, the first rotation angle, the second rotation angle, the third rotation angle, the second distance, the third distance, and the radius of the driving wheel. The sum of the kinetic energy of the driving wheel, the kinetic energy of the wheel leg, and the kinetic energy of the robot body is determined as the kinetic energy of the wheel-legged robot corresponding to the state parameter.

[0190] In one possible implementation, the energy parameter determination module 1401 is configured to determine the angular velocity of the driving wheel based on the third rotation angle, determine the translational velocity of the driving wheel based on the angular velocity of the driving wheel and the radius of the driving wheel, and determine the kinetic energy of the driving wheel based on the mass of the driving wheel, the angular velocity of the driving wheel, and the translational velocity of the driving wheel.

[0191] In one possible implementation, the energy parameter determination module 1401 is configured to determine the angular velocity of the wheel leg based on the first rotation angle, determine the translational velocity of the wheel leg based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the first rotation angle, and the first distance, and determine the kinetic energy of the wheel leg based on the mass of the wheel leg, the angular velocity of the wheel leg, and the translational velocity of the wheel leg.

[0192] In one possible implementation, the energy parameter determination module 1401 is configured to determine the angular velocity of the robot body based on the second rotation angle and the angular velocity of the wheel leg. Determine the translational velocity of the robot body based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the angular velocity of the robot body, the second distance, the third distance, the first rotation angle, the second rotation angle, the second distance, and the third distance. Determine the kinetic energy of the robot body based on the mass of the robot body, the angular velocity of the robot body, and the translational velocity of the robot body.

[0193] In one possible embodiment, the first constraint relationship data includes first relationship data and second relationship data. The first constraint relationship data determining module 1402 is configured to establish, for any set of energy parameters from the multiple sets of energy parameters, first relationship data between the kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters and a third rotation angle, where the third rotation angle is the rotation angle of the driving wheel. Second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the first torque are established based on the kinetic energy of the wheel-legged robot in the energy parameters, the first rotation angle, and the potential energy of the wheel-legged robot in the energy parameters, where the first rotation angle is the rotation angle of the wheel-legged robot in the target space. Second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the second torque are established based on the kinetic energy of the wheel-legged robot in the energy parameters, the second rotation angle, and the potential energy of the wheel-legged robot in the energy parameters, where the second rotation angle is the rotation angle of the robot body relative to the wheel-legged robot.

[0194] In one possible implementation, the first constraint relationship data determination module 1402 is configured to obtain a first driving wheel partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the angular velocity of the driving wheel, where the angular velocity of the driving wheel is determined based on the third rotation angle. Furthermore, the module 1402 is configured to obtain a second driving wheel partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the third rotation angle. Furthermore, the module 1402 is configured to obtain a first time partial derivative of the second driving wheel partial derivative with respect to time. The first relationship data is established based on the first time partial derivative and the first driving wheel partial derivative.

[0195] In one possible implementation, the first constraint relationship data determination module 1402 is configured to obtain a first wheel-leg partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the angular velocity of the wheel-legged robot, where the angular velocity of the wheel-legged robot is determined based on the first rotation angle. Furthermore, the module 1402 is configured to obtain a second wheel-leg partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the first rotation angle. Furthermore, the module 1402 is configured to obtain a second time partial derivative of the second wheel-leg partial derivative with respect to time. Furthermore, the module 1402 is configured to establish the second relationship data based on the second time partial derivative and the first wheel-leg partial derivative.

[0196] In one possible implementation, the first constraint relationship data determination module 1402 is configured to obtain a first robot-body partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the angular velocity of the robot body, where the angular velocity of the robot body is determined based on the first rotation angle and the second rotation angle. Furthermore, the module 1402 is configured to obtain a second robot-body partial derivative of the wheel-legged robot's kinetic energy in the energy parameter with respect to the second rotation angle. Furthermore, the module 1402 is configured to obtain a third time partial derivative of the second robot-body partial derivative with respect to time. Furthermore, the module 1402 is configured to establish the second constraint relationship data based on the third time partial derivative and the first robot-body partial derivative.

[0197] In one possible embodiment, the second constraint relationship data determination module 1403 is used to establish the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data, the value range of the state parameter, the value range of the first torque, and the value range of the second torque.

[0198] In a possible embodiment, the state parameters include a first rotation angle, a second rotation angle, a third rotation angle, the angular velocity of the driving wheel, the angular velocity of the wheel leg and the angular velocity of the robot body, the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, and the third rotation angle is the angle of rotation of the driving wheel. The second constraint relationship data determination module 1403 is used to establish, within the value range of the state parameter and the value range of the first torque, the constraint relationship data between the first torque of the first motor and the third rotation angle, the angular velocity of the driving wheel, the first rotation angle and the angular velocity of the wheel leg based on the first constraint relationship data. The terminal establishes, within the value range of the state parameter and the value range of the second torque, the constraint relationship data between the second torque of the second motor and the second rotation angle and the angular velocity of the robot body based on the second constraint relationship data.

[0199] It should be noted that the apparatus for determining constraint relationship data for a wheel-legged robot provided in the above embodiment only uses the division of the above-mentioned functional modules as an example when determining the constraint relationship data for the wheel-legged robot. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus for determining constraint relationship data for a wheel-legged robot provided in the above embodiment and the embodiment of the method for determining constraint relationship data for a wheel-legged robot are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0200] Through the technical solutions provided in the embodiments of the present application, before the wheel-legged robot is manufactured, multiple sets of energy parameters are determined based on multiple state parameters of the active wheels, wheel legs, and robot body of the wheel-legged robot. These multiple sets of energy parameters can reflect the potential energy and kinetic energy of the wheel-legged robot in different states. Determining the first constraint relationship data and the second constraint relationship data based on multiple energy parameters conforms to the basic laws of physics. Through the first constraint relationship data, the second constraint relationship data, and these multiple sets of state parameters, constraint relationship data between the state parameters of the wheel-legged robot and the first torque and the second torque can be established. In this way, after the wheel-legged robot is manufactured, this constraint relationship data can be directly imported, thereby improving the research and development efficiency of the wheel-legged robot.

[0201] The present application embodiment provides a computer device for executing the above method. The computer device can be implemented as a terminal or a server. The structure of the terminal is first introduced below:

[0202] Figure 15 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present application.

[0203] Typically, the terminal 1500 includes: one or more processors 1501 and one or more memories 1502 .

[0204] The processor 1501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 1501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 1501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0205] The memory 1502 may include one or more computer-readable storage media, which may be non-transitory. The memory 1502 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1502 is used to store at least one computer program, which is executed by the processor 1501 to implement the method for determining the constraint relationship data of the wheel-legged robot provided in the method embodiment of the present application.

[0206] In some embodiments, terminal 1500 may optionally include a peripheral device interface 1503 and at least one peripheral device. The processor 1501, memory 1502, and peripheral device interface 1503 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 1503 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 1504, a display screen 1505, a camera assembly 1506, an audio circuit 1507, and a power supply 1508.

[0207] The peripheral device interface 1503 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 1501 and the memory 1502. In some embodiments, the processor 1501, the memory 1502, and the peripheral device interface 1503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1501, the memory 1502, and the peripheral device interface 1503 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0208] RF circuit 1504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. RF circuit 1504 communicates with communication networks and other communication devices via electromagnetic signals. RF circuit 1504 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. RF circuit 1504 may optionally include an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like.

[0209] Display screen 1505 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1505 is a touch screen display, display screen 1505 also has the ability to collect touch signals on or above the surface of display screen 1505. The touch signals can be input as control signals to processor 1501 for processing. In this case, display screen 1505 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards.

[0210] The camera assembly 1506 is used to collect images or videos. Optionally, the camera assembly 1506 includes a front camera and a rear camera. Typically, the front camera is set on the front panel of the terminal, and the rear camera is set on the back of the terminal.

[0211] The audio circuit 1507 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals that are input to the processor 1501 for processing, or input to the radio frequency circuit 1504 for voice communication.

[0212] The power supply 1508 is used to supply power to various components in the terminal 1500. The power supply 1508 can be alternating current, direct current, a disposable battery, or a rechargeable battery.

[0213] In some embodiments, the terminal 1500 further includes one or more sensors 1509 , including but not limited to: an acceleration sensor 1510 , a gyroscope sensor 1511 , a pressure sensor 1512 , an optical sensor 1513 , and a proximity sensor 1514 .

[0214] The acceleration sensor 1510 can detect acceleration magnitudes on three coordinate axes of a coordinate system established with the terminal 1500 .

[0215] The gyro sensor 1511 can detect the body direction and rotation angle of the terminal 1500 . The gyro sensor 1511 can cooperate with the acceleration sensor 1510 to collect the user's 3D actions on the terminal 1500 .

[0216] The pressure sensor 1512 can be provided on the side frame of the terminal 1500 and / or below the display screen 1505. When the pressure sensor 1512 is provided on the side frame of the terminal 1500, it can detect the user's gripping signal of the terminal 1500, and the processor 1501 can perform left and right hand recognition or shortcut operations based on the gripping signal collected by the pressure sensor 1512. When the pressure sensor 1512 is provided below the display screen 1505, the processor 1501 controls the operable controls on the UI interface based on the user's pressure operation on the display screen 1505.

[0217] The optical sensor 1513 is used to collect the ambient light intensity. In one embodiment, the processor 1501 can control the display brightness of the display screen 1505 according to the ambient light intensity collected by the optical sensor 1513.

[0218] The proximity sensor 1514 is used to collect the distance between the user and the front of the terminal 1500 .

[0219] Those skilled in the art will understand that Figure 15 The structure shown in the figure does not constitute a limitation on the terminal 1500, and the terminal 1500 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0220] The above-mentioned computer device can also be implemented as a server. The structure of the server is introduced below:

[0221] Figure 16 This is a structural diagram of a server provided in an embodiment of the present application. The server 1600 may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 1601 and one or more memories 1602, wherein the one or more memories 1602 store at least one computer program, and the at least one computer program is loaded and executed by the one or more processors 1601 to implement the methods provided in the above-mentioned various method embodiments. Of course, the server 1600 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The server 1600 may also include other components for implementing device functions, which will not be described in detail here.

[0222] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including a computer program. The computer program can be executed by a processor to implement the method for determining constraint relationship data of the wheel-legged robot in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, or the like.

[0223] In an exemplary embodiment, a computer program product or computer program is also provided, which includes a program code, which is stored in a computer-readable storage medium. A processor of a computer device reads the program code from the computer-readable storage medium, and the processor executes the program code, so that the computer device executes the above-mentioned method for determining the constraint relationship data of the wheel-legged robot.

[0224] In some embodiments, the computer program involved in the embodiments of the present application may be deployed and executed on a computer device, or on multiple computer devices located at one location, or on multiple computer devices distributed at multiple locations and interconnected through a communication network. Multiple computer devices distributed at multiple locations and interconnected through a communication network may constitute a blockchain system.

[0225] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or may be accomplished by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0226] The above are only optional 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 principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for determining constraint relationship data of a wheel-legged robot, characterized in that: The wheel-legged robot includes a driving wheel, a wheel leg, and a robot body, wherein the driving wheel and the wheel leg are connected via a first motor, and the robot body and the wheel leg are connected via a second motor. The method includes: Determining multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the active wheel, the wheel-legged robot, and the robot body, each set of energy parameters including potential energy and kinetic energy of the wheel-legged robot, the multiple sets of state parameters corresponding to multiple states of the wheel-legged robot; Based on multiple sets of energy parameters of the wheel-legged robot, determining first constraint relationship data of the first motor and second constraint relationship data of the second motor, the first constraint relationship data being used to represent a mathematical relationship between a first torque and the energy parameter of the first motor, and the second constraint relationship data being used to represent a mathematical relationship between a second torque and the energy parameter of the second motor; Based on the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters, the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor are determined, and the constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor.

2. The method according to claim 1, characterized in that The determining of the multiple sets of energy parameters of the wheel-legged robot based on the multiple sets of state parameters of the driving wheel, the wheel legs, and the robot body comprises: For any set of state parameters among the multiple sets of state parameters, determine the potential energy of the wheel-legged robot corresponding to the state parameters based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance, the mass of the wheel leg, and the mass of the robot body in the state parameters, wherein the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, the first distance is the distance between the center of mass of the wheel leg and the first connection point, the second distance is the distance between the center of mass of the robot body and the second connection point, and the third distance is the distance between the first connection point and the second connection point. The first connection point is the connection point between the wheel leg and the driving wheel, and the second connection point is the connection point between the robot body and the wheel leg. Based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance, the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body and the radius of the driving wheel in the state parameters, the kinetic energy of the wheel-legged robot corresponding to the state parameters is determined, and the third rotation angle is the angle of rotation of the driving wheel.

3. The method according to claim 2, characterized in that Determining the potential energy of the wheel-legged robot corresponding to the state parameters based on the first rotation angle, the second rotation angle, the first distance, the second distance, the third distance, the mass of the wheel-leg, and the mass of the robot body includes: determining a first potential energy of the robot body based on the mass of the robot body, the third distance, and the first rotation angle; determining a second potential energy of the robot body based on the mass of the robot body, the second distance, the first rotation angle, and the second rotation angle; determining a potential energy of the wheel leg based on the mass of the wheel leg, the first distance, and the first rotation angle; The sum of the first potential energy, the second potential energy and the potential energy of the wheel-leg is determined as the potential energy of the wheel-legged robot corresponding to the state parameter.

4. The method according to claim 2, characterized in that Determining the kinetic energy of the wheel-legged robot corresponding to the state parameters based on the first rotation angle, the second rotation angle, the third rotation angle, the first distance, the second distance, the third distance, the mass of the driving wheel, the mass of the wheel leg, the mass of the robot body, and the radius of the driving wheel includes: determining the kinetic energy of the driving wheel based on the mass of the driving wheel, the third rotation angle, and the radius of the driving wheel; determining the kinetic energy of the wheel leg based on the mass of the wheel leg, the first rotation angle, the first distance, the third rotation angle, and the radius of the driving wheel; determining the kinetic energy of the robot body based on the mass of the robot body, the first rotation angle, the second rotation angle, the third rotation angle, the second distance, the third distance, and the radius of the driving wheel; The sum of the kinetic energy of the driving wheel, the kinetic energy of the wheel-leg and the kinetic energy of the robot body is determined as the kinetic energy of the wheel-leg robot corresponding to the state parameter.

5. The method according to claim 4, characterized in that The determining of the kinetic energy of the driving wheel based on the mass of the driving wheel, the third rotation angle, and the radius of the driving wheel includes: determining an angular velocity of the driving wheel based on the third rotation angle; Determining a translational velocity of the driving wheel based on the angular velocity of the driving wheel and the radius of the driving wheel; The kinetic energy of the driving wheel is determined based on the mass of the driving wheel, the angular velocity of the driving wheel, and the translational velocity of the driving wheel.

6. The method according to claim 5, characterized in that The determining of the kinetic energy of the wheel leg based on the mass of the wheel leg, the first rotation angle, the first distance, the third rotation angle, and the radius of the driving wheel includes: determining an angular velocity of the wheel leg based on the first rotation angle; Determining a translational velocity of the wheel leg based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the first rotation angle, and the first distance; The kinetic energy of the wheel leg is determined based on the mass of the wheel leg, the angular velocity of the wheel leg, and the translational velocity of the wheel leg.

7. The method according to claim 6, characterized in that The determining the kinetic energy of the robot body based on the mass of the robot body, the first rotation angle, the second rotation angle, the third rotation angle, the second distance, the third distance, and the radius of the driving wheel includes: determining an angular velocity of the robot body based on the second rotation angle and the angular velocity of the wheel leg; Determining a translational velocity of the robot body based on the angular velocity of the driving wheel, the radius of the driving wheel, the angular velocity of the wheel leg, the angular velocity of the robot body, the second distance, the third distance, the first rotation angle, the second rotation angle, the second distance, and the third distance; The kinetic energy of the robot body is determined based on the mass of the robot body, the angular velocity of the robot body, and the translational velocity of the robot body.

8. The method according to claim 1, characterized in that The first constraint relationship data includes first relationship data and second relationship data, and determining the first constraint relationship data of the first motor and the second constraint relationship data of the second motor based on the multiple sets of energy parameters of the wheel-legged robot includes: For any one of the multiple sets of energy parameters, establishing the first relationship data between the kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters and a third rotation angle, wherein the third rotation angle is the angle of rotation of the driving wheel; establishing second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters, a first rotation angle, and the potential energy of the wheel-legged robot in the energy parameters, wherein the first rotation angle is the rotation angle of the wheel-legged robot in the target space; Based on the kinetic energy, the second rotation angle and the potential energy of the wheel-legged robot in the energy parameters, the second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the second torque are established, and the second rotation angle is the rotation angle of the robot body relative to the wheel leg.

9. The method according to claim 8, characterized in that The establishing of the first relationship data between the kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy of the wheel-legged robot in the energy parameters and the third rotation angle includes: Obtaining a first driving wheel partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the angular velocity of the driving wheel, where the angular velocity of the driving wheel is determined based on the third rotation angle; Obtaining a second driving wheel partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the third rotation angle; Obtaining a first time partial derivative of the second driving wheel partial derivative with respect to time; The first relationship data is established based on the first time partial derivative and the first driving wheel partial derivative.

10. The method according to claim 8, characterized in that The establishing of the second relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the first torque based on the kinetic energy and the first rotation angle of the wheel-legged robot in the energy parameters and the potential energy of the wheel-legged robot in the energy parameters comprises: Obtaining a first wheel-leg partial derivative of the kinetic energy of the wheel-leg type robot in the energy parameter with respect to the angular velocity of the wheel-leg, where the angular velocity of the wheel-leg is determined based on the first rotation angle; Obtaining a second wheel-leg partial derivative of the kinetic energy of the wheel-legged robot with respect to the first rotation angle in the energy parameter; Obtaining a second time partial derivative of the second leg partial derivative with respect to time; The second relationship data is established based on the second time partial derivative and the first wheel-leg partial derivative.

11. The method according to claim 8, characterized in that The establishing of the second constraint relationship data between the potential energy and kinetic energy of the wheel-legged robot in the energy parameters and the second torque based on the kinetic energy and the second rotation angle of the wheel-legged robot in the energy parameters and the potential energy of the wheel-legged robot in the energy parameters comprises: Obtaining a first robot body partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the angular velocity of the robot body, wherein the angular velocity of the robot body is determined based on the first rotation angle and the second rotation angle; Obtaining a second robot body partial derivative of the kinetic energy of the wheel-legged robot in the energy parameter with respect to the second rotation angle; Obtaining a third time partial derivative of the second robot body partial derivative with respect to time; The second constraint relationship data is established based on the third time partial derivative and the first robot body partial derivative.

12. The method according to claim 1, characterized in that The determining, based on the first constraint relationship data, the second constraint relationship data, and the multiple sets of state parameters, the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor comprises: Based on the first constraint relationship data, the second constraint relationship data, the value range of the state parameter, the value range of the first torque and the value range of the second torque, constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor are established.

13. The method according to claim 12, characterized in that The state parameters include a first rotation angle, a second rotation angle, a third rotation angle, an angular velocity of the driving wheel, an angular velocity of the wheel leg, and an angular velocity of the robot body, wherein the first rotation angle is the rotation angle of the wheel leg in the target space, the second rotation angle is the rotation angle of the robot body relative to the wheel leg, and the third rotation angle is the angle of rotation of the driving wheel. The constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor, and the second torque of the second motor, established based on the first constraint relationship data, the second constraint relationship data, the value range of the state parameters, the value range of the first torque, and the value range of the second torque, includes: Establishing, within the value range of the state parameter and the value range of the first torque, constraint relationship data between the first torque of the first motor and the third rotation angle, the angular velocity of the driving wheel, the first rotation angle, and the angular velocity of the wheel leg based on the first constraint relationship data; Within the value range of the state parameter and the value range of the second torque, constraint relationship data between the second torque of the second motor and the second rotation angle and the angular velocity of the robot body are established based on the second constraint relationship data.

14. A device for determining constraint relationship data of a wheel-legged robot, characterized in that: The wheel-legged robot comprises a driving wheel, a wheel leg and a robot body, wherein the driving wheel and the wheel leg are connected via a first motor, and the robot body and the wheel leg are connected via a second motor. The device comprises: an energy parameter determination module, configured to determine multiple sets of energy parameters of the wheel-legged robot based on multiple sets of state parameters of the active wheels, the wheel legs, and the robot body, each set of energy parameters comprising potential energy and kinetic energy of the wheel-legged robot, the multiple sets of state parameters corresponding to multiple states of the wheel-legged robot; a first constraint relationship data determination module, configured to determine first constraint relationship data of the first motor and second constraint relationship data of the second motor based on multiple sets of energy parameters of the wheel-legged robot, wherein the first constraint relationship data is used to represent a mathematical relationship between a first torque and the energy parameter of the first motor, and the second constraint relationship data is used to represent a mathematical relationship between a second torque and the energy parameter of the second motor; A second constraint relationship data determination module is used to determine the constraint relationship data between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor based on the first constraint relationship data, the second constraint relationship data and the multiple sets of state parameters. The constraint relationship data is used to represent the mathematical relationship between the state parameters of the wheel-legged robot, the first torque of the first motor and the second torque of the second motor.

15. A computer device, characterized in that: The computer device includes one or more processors and one or more memories, and at least one computer program is stored in the one or more memories. The computer program is loaded and executed by the one or more processors to implement the method for determining the constraint relationship data of the wheel-legged robot as described in any one of claims 1 to 13.

16. A computer-readable storage medium, characterized in that At least one computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by the processor to implement the method for determining the constraint relationship data of the wheel-legged robot according to any one of claims 1 to 13.

17. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the method for determining the constraint relationship data of the wheel-legged robot according to any one of claims 1 to 13.

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