A method and system for optimizing the whole-body trajectory of a quadruped single-arm operating robot

Abstract

The application discloses a kind of four-foot single-arm operation robot whole body movement trajectory optimization method and system, it is related to four-foot single-arm robot control technical field, this method includes: respectively establishing the kinematic model of robot four limbs and operation arm and the dynamics model of trunk centroid;The movement gait of robot is described using continuous time variable, the movement of robot is decomposed into trunk centroid movement, leg movement, operation arm movement, the movement curve of each movement is described, and the constraint condition that is received in the movement process of robot is constructed;Wherein, time variable is the phase duration of robot;According to the current state of robot and the set desired operation target, joint kinematic model, dynamics model, movement gait, the movement curve of each movement after decomposition and the constraint condition of robot movement, establish the whole body movement trajectory nonlinear optimization problem of robot operation, use optimization solving library to solve problem, obtain optimal movement trajectory.

Description

Technical Field

[0001] This invention relates to the field of quadrupedal single-arm robot control technology, and in particular to a method and system for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Motion planning is a fundamental problem in legged robotics research and a crucial component of legged robot controllers. Motion planning for legged robots is extremely challenging. Firstly, trunk movement cannot be directly generated; it requires discontinuous contact between the robot's legs and the environment. Secondly, legged robots are generally high-degree-of-freedom systems, and the sheer number of degrees of freedom that motion planning needs to handle makes the planning process very difficult. Building on this, quadrupedal single-arm robots integrate the structure of legs and a working arm, increasing not only the overall number of degrees of freedom of the system but also adding more constraints to the working arm, including self-collision, posture maintenance, and singularity avoidance. Therefore, motion planning for systems like quadrupedal single-arm robots is particularly difficult.

[0004] Motion trajectory planning for quadrupedal single-arm robots requires solving the overall or whole-body motion planning problem, solving for the desired motion encompassing all degrees of freedom. Due to the large number of degrees of freedom in quadrupedal single-arm robots—6 degrees of freedom for the torso, 12 for the leg joints, and 6 for the working arm joints, totaling 24 degrees of freedom—the equations governing their motion states are extremely complex, making motion planning difficult. Early quadrupedal single-arm robot motion planning often relied on static stability as a criterion, manually setting and adjusting feasible trajectories for torso, foot movements, forces, and other related quantities. The interaction force between the working arm's end effector and the environment was considered constant and included in the stability assessment. However, this approach requires manual control and cannot achieve unmanned intelligent operation of the robot. Currently, other planning methods have been proposed: using dynamic stability criteria to plan the contact positions and contact forces of the entire robot, with its working arm used to assist in maintaining the robot's stability and completing the task. However, these methods usually face problems such as complex motion processes that are difficult to represent, too many model parameters, and excessive computation time, making online planning impossible. Teleoperation is another method, where the desired motion target is set manually, and the motion of the torso and working arm is planned independently. However, this type of teleoperation method reduces the robot's autonomous performance and cannot achieve unmanned intelligent operation of the robot. Summary of the Invention

[0005] To address the shortcomings of the existing technologies, this invention provides a method and system for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot. Given a desired operational objective, this method solves the optimal whole-body motion trajectory under various complex terrains by constructing a nonlinear problem for optimizing the robot's whole-body motion trajectory. This solves the problems of traditional trajectory planning methods, such as the inability to continuously represent complex discrete motion processes, the large amount of model parameter adjustment, and the complexity of gait sequence design. Ultimately, this method achieves optimal planning and stable motion control for the quadrupedal single-arm robot's operational motion.

[0006] In a first aspect, the present invention provides a method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot.

[0007] A method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot includes:

[0008] For a quadruped single-arm robot, kinematic models of the robot's limbs and working arm, as well as a dynamic model of the trunk's center of mass, are established respectively.

[0009] The robot's gait is described using a continuous time variable. The robot's motion is decomposed into trunk center of mass motion, leg motion, and working arm motion. The motion curves of each motion are described, and the constraints on the robot's motion are constructed. The time variable is the robot phase duration.

[0010] Based on the robot's current state and the set expected task objectives, a nonlinear optimization problem for the robot's whole-body motion trajectory is established by combining the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints on the robot's motion. The optimal motion trajectory is obtained by using an optimization solution library.

[0011] Secondly, the present invention provides a whole-body motion trajectory optimization system for a quadrupedal single-arm robot.

[0012] A method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot includes:

[0013] The modeling module is used to create kinematic models of the robot's limbs and working arm, as well as a dynamic model of the trunk's center of mass for a quadrupedal single-arm robot.

[0014] The motion analysis module is used to describe the robot's gait using continuous time variables. It decomposes the robot's motion into trunk center of mass motion, leg motion, and working arm motion, describes the motion curves of each motion, and constructs the constraints on the robot during its motion. The time variable is the robot phase duration.

[0015] The optimal motion trajectory generation module is used to establish a nonlinear optimization problem of the robot's whole-body motion trajectory based on the robot's current state and the set expected task objective, by combining the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints of the robot's motion. The optimal motion trajectory is obtained by solving the problem using an optimization solution library.

[0016] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the above-described method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot.

[0017] Fourthly, the present invention also provides a computer-readable storage medium storing executable instructions for causing a processor to execute the executable instructions to implement the above-described method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot.

[0018] Fifthly, the present invention also provides a computer program product comprising executable instructions stored in a computer-readable storage medium; wherein, when the processor of the electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, it implements the above-mentioned method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot.

[0019] The above one or more technical solutions have the following beneficial effects:

[0020] 1. This invention provides a method and system for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot. It establishes the kinematic equations for the robot's limbs and the working arm, and the dynamic equations for the trunk's center of mass. Continuous time variables are used to describe the robot's main motion parameters, and a nonlinear optimization problem (NLP) is employed to describe the robot's whole-body motion process, which contains discrete processes. The optimal solution yields the robot's whole-body motion trajectory, solving the whole-body motion trajectory planning problem for a quadrupedal single-arm robot. This ensures the executability and robustness of the trajectory, achieving optimized planning and stable motion control for the quadrupedal single-arm robot's operation.

[0021] 2. The whole-body motion trajectory optimization method for a quadrupedal single-arm robot proposed in this invention can solve the optimal whole-body motion trajectory under various complex terrains such as steps, slopes, and ravines, given the desired work objective. This solves the problems of complex discrete motion processes that cannot be continuously represented, large amount of model parameter adjustment, and complex gait sequence design in traditional trajectory planning methods.

[0022] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0023] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0024] Figure 1 This is a flowchart of the whole-body motion trajectory optimization method for the quadrupedal single-arm robot described in an embodiment of the present invention;

[0025] Figure 2 This is a schematic diagram illustrating the atypical diagonal trotting state of the quadrupedal single-arm robot in an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of the movement trajectory of the quadrupedal single-arm robot traversing stepped terrain in an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram of the movement trajectory of the quadrupedal single-arm robot traversing ravine terrain in an embodiment of the present invention;

[0028] Figure 5 This is a schematic diagram of the movement trajectory of a quadrupedal single-arm robot traversing a sloping terrain in an embodiment of the present invention. Detailed Implementation

[0029] It should be noted that the following detailed descriptions are exemplary and are intended only to describe specific embodiments and to provide further explanation of the invention, and are not intended to limit the scope of exemplary embodiments of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] Terminology Explanation:

[0031] NLP: nonlinear programming problem;

[0032] Ipopt: Interior Point Optimizer.

[0033] Example 1

[0034] This embodiment provides a method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot, such as... Figure 1 As shown, it includes the following steps:

[0035] Step S1: For the quadrupedal single-arm robot, establish the kinematic models of the robot's limbs and working arm, as well as the dynamic model of the trunk's center of mass.

[0036] Step S1.1: For a quadrupedal single-arm robot, considering that the robot consists of two parts: limbs and a working arm, both parts should be considered during operation or movement. Therefore, in this embodiment, forward kinematic models of the robot's limbs and working arm are established separately, which can be represented as:

[0037]

[0038] in, This indicates the position of the i-th end in the world coordinate system; i = 0, 1, 2, 3 represent the feet of the four legs, and i = 4 represents the end of the working arm; n s The dimension representing the end-effector pose; when using linear position, n s =3, while when using generalized position, n s =6, which includes the position and orientation of the end effector in the world coordinate system; These correspond to the state variables of the entire robot, the torso, the i-th leg, and the working arm, respectively; h l,i (q l,i ) represents the forward kinematics of the i-th leg in the torso coordinate system; h m (q m ) represents the forward kinematics of the working arm in the torso coordinate system; This represents the transformation matrix from the torso coordinate system to the world coordinate system.

[0039] Step S1.2: For the quadrupedal single-arm robot, establish the dynamic equations of the torso in Cartesian space, i.e., establish the dynamic model of the torso's center of mass. In this embodiment, the simplified dynamic function f at the torso's center of mass is constructed. SRBD (r,f,p) can be represented as:

[0040]

[0041] In the above formula, m represents the weight of the robot's torso, and g represents the acceleration due to gravity. Let ω(t) represent the linear acceleration at the center of mass, where t is the time variable and ω(t) is the angular velocity of the center of mass. I represents angular acceleration. b f represents the inertial parameter of the torso. i (t) represents the equivalent force at the center of mass of the torso corresponding to the i-th end, which comes from the force of the supporting leg against the ground and the interaction force between the end of the robotic arm and the work object, f i The product of p(t) and the corresponding force arm r(t) represents the equivalent torque. i(t) represents the position of the i-th end at time t.

[0042] Step S2: Describe the robot's gait using continuous time variables; where the time variable is the duration of the robot phase.

[0043] In this embodiment, the robot's contact state is described using continuous phase durations, thereby obtaining a description of the robot's gait. Here, the robot's phase refers to the continuous swinging or supporting state of each leg. Based on this, the gait can be represented graphically, with the time variable defined as ΔT. i,j i = 1, 2, 3, 4, 5, j = 1, 2, 3, 4. In this embodiment, the quadrupedal single-arm robot has five possible contact points, therefore the defined phase sequence combinations are at most 2. 5 =32 possible outcomes, such as Figure 2 The diagram shows an atypical diagonal trotting motion, in which the working arm remains airborne throughout.

[0044] Step S3: Decompose the robot's motion into trunk center of mass motion, leg motion, and working arm motion, and describe the motion curves of each motion.

[0045] In this embodiment, the robot's motion is decomposed into three sub-modules: trunk center of mass motion, leg motion, and working arm motion. The leg motion can be further subdivided into supporting leg motion and swinging leg motion. Based on this, the motion curves of each motion can be described as the trunk center of mass quadrupole motion curve, the leg cubic motion curve (including the supporting leg fixed state equation and the swinging leg cubic force motion curve), and the working arm cubic motion curve, etc.

[0046] (1) The linear motion curve of the center of mass can be described as the quartic motion of the trunk's center of mass, defined in the x-direction as:

[0047]

[0048] Among them, a i The coefficients representing the curve, i = 0, ..., 4, are determined through optimization. The position of the linear centroid of the torso is indicated by three directions: x, y, and z. The x-direction is...

[0049] (2) The leg motion curve can be further subdivided into supporting leg motion and swinging leg motion. Among them, the foot position of the supporting leg needs to remain unchanged relative to the world coordinate system, so a fixed value is used, which can be expressed as:

[0050] p i (t∈C i,s ) = p i,s =const

[0051] In the above formula, const represents a fixed constant value, C i,s This indicates that the i-th leg is in a supporting state, and s is an auxiliary selection variable. In fact, the above formula can be used as a non-sliding constraint to restrict the motion state of the supporting leg.

[0052] Therefore, the foot motion during the swing phase is described by a cubic polynomial, that is, by a cubic force curve at the end of the contacting limb, which can be expressed as:

[0053]

[0054] In the above formula, the position vector p i (t) and curve parameter vector The time vector η(t) can be further expressed as:

[0055] p i (t)=[p i,x (t)p i,y (t)p i,z (t)] T

[0056]

[0057] η(t)=[1t t 2 t 3 ]

[0058] (3) The motion curve of the boom can be described as a cubic curve motion of the boom, which can be expressed as:

[0059]

[0060] In the above formula, Indicates the position of the end of the boom. This indicates the posture of the end effector of the boom, with the subscript m representing the boom.

[0061] Step S4: Construct the constraints that the robot experiences during its movement.

[0062] In this embodiment, the constraint equations experienced by the robot during its motion are established, including contact constraints, non-contact constraints, kinematic constraints, terrain constraints, phase-time constraints, etc., specifically as follows:

[0063] (1) When the robot's limbs come into contact with the environment, contact constraints must be satisfied, including force constraints and friction cone constraints. The expression for these constraints is as follows:

[0064]

[0065]

[0066] in, f represents the position of the i-th foot in the x and y directions. T (t) represents the thrust vector generated by the foot on the ground. This represents the direction vector at the x, y position on the terrain surface. f represents gravity, which is related to the robot's mass. n (t) represents the scalar quantity of thrust, C i,s t1 and t2 indicate whether the i-th leg is in the support phase at time s; t1 and t2 represent the two tangential directions, and μ is the coefficient of friction.

[0067] Furthermore, when the robot's limbs do not come into contact with the environment, the non-contact constraint is satisfied, which can be expressed as:

[0068]

[0069] Among them, f i This represents the force acting on the i-th end. This indicates the moment when the i-th end does not support the phase.

[0070] (2) Kinematic constraints include those for the limbs and the working arm. These constraints are essentially constraints on the reachable space of the limbs' ends. Specifically, the kinematic constraints for the limbs are expressed as follows: No leg exceeds the range of the cube corresponding to the current index, which can be represented as:

[0071]

[0072] Where R(θ) represents the rotation matrix from the world coordinate system to the torso coordinate system; q i Let b represent the joint vector of the i-th leg. min,i and b max,i These represent the upper and lower limits for each joint, respectively. This represents the transformation matrix from the torso coordinate system to the world coordinate system.

[0073] Then, the kinematic constraints of the working arm can be expressed as:

[0074]

[0075] Where p4 represents the position of the end effector of the working arm relative to the world coordinate system. This indicates the reference point of the working arm in the workspace, with the reference coordinate axes parallel to the coordinate axes of the world coordinate system; b represents the unit direction vector in the world coordinate system; ee It is a 1×3 row vector containing the dimension values ​​of the cube constraint.

[0076] (3) Since this embodiment does not involve the acquisition of terrain information, it is assumed that the terrain data is known, denoted as h. terrain (x,y), and thus the terrain constraint equations related to the terrain of the supporting leg can be defined as follows:

[0077]

[0078] in, This indicates the position of the i-th foot tip in the z-direction. The terrain information represents the position of the i-th foot tip in the x and y directions.

[0079] (4) In addition, this embodiment also includes a phase-time constraint, which is expressed as follows:

[0080]

[0081] Where, ΔT i,j Let i be the time variable, i = 1, 2, 3, 4, 5, j = 1, 2, 3, 4, and T be the total time of an entire gait.

[0082] Step S5: Based on the robot's current state and the set expected task objective, combine the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints of the robot's motion to establish a nonlinear optimization problem for the robot's whole-body motion trajectory. Use an optimization solution library to solve the problem and obtain the optimal motion trajectory.

[0083] Specifically, based on the robot's current state and the set desired task objective, the robot's initial and final positions are determined. By combining the aforementioned kinematic model, dynamic model, gait, motion curves of the decomposed motions, and constraints on the robot's motion, a nonlinear optimization problem is formed. In this embodiment, considering the conditions listed above, the robot's whole-body task trajectory optimization problem is established, which can be expressed as:

[0084]

[0085] Furthermore, an optimization solution library is used to solve for the optimal trajectory. In this embodiment, the existing numerical optimization open-source library Ipopt is called to solve for the optimal solution of the above equation, thereby obtaining the robot's center of mass position, torso posture, phase time, foot position, and foot force during the movement process. The robot's gait sequence, step time, foot landing point, swing leg movement trajectory, working arm movement trajectory, and torso movement trajectory are obtained, thus obtaining the robot's optimal whole-body movement trajectory.

[0086] The motion trajectory optimization method for the quadrupedal single-arm robot proposed in this embodiment can solve for the full-body motion trajectory under various complex terrains such as steps, slopes, and ravines, given the desired task objective. The motion trajectories are as follows: Figure 3 , Figure 4 , Figure 5 As shown, it can realize the optimized planning of operation motion and stable motion control of quadrupedal single-arm robot.

[0087] Example 2

[0088] This embodiment provides a method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot, including:

[0089] The modeling module is used to create kinematic models of the robot's limbs and working arm, as well as a dynamic model of the trunk's center of mass for a quadrupedal single-arm robot.

[0090] The motion analysis module is used to describe the robot's gait using continuous time variables. It decomposes the robot's motion into trunk center of mass motion, leg motion, and working arm motion, describes the motion curves of each motion, and constructs the constraints on the robot during its motion. The time variable is the robot phase duration.

[0091] The optimal motion trajectory generation module is used to establish a nonlinear optimization problem of the robot's whole-body motion trajectory based on the robot's current state and the set expected task objective, by combining the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints of the robot's motion. The optimal motion trajectory is obtained by solving the problem using an optimization solution library.

[0092] Example 3

[0093] This embodiment provides an electronic device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the method provided in this embodiment.

[0094] Example 4

[0095] This embodiment also provides a computer-readable storage medium storing executable instructions, which, when executed by a processor, will cause the processor to execute the method described above in this embodiment.

[0096] Example 5

[0097] This embodiment provides a computer program product including executable instructions, which are computer instructions; the executable instructions are stored in a computer-readable storage medium. When the processor of an electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the electronic device performs the method described in this embodiment.

[0098] The steps and methods involved in Embodiments 2 to 5 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0099] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0100] The above description is only a preferred embodiment of the present invention. Although the specific embodiments of the present invention have been described in conjunction with the accompanying drawings, they are not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solutions of the present invention, various modifications or variations that can be made by those skilled in the art without creative effort are still within the scope of protection of the present invention.

Claims

1. A method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot, characterized in that, include: For a quadrupedal single-arm robot, kinematic models of the robot's limbs and working arm, as well as a dynamic model of the torso's center of mass, are established. The forward kinematic models of the robot's limbs and working arm are represented as follows: in, Indicates the first The position of each end in the world coordinate system; It represents the feet of four legs. Indicates the end of the working arm; The dimension representing the end-effector pose, when using linear position, When using generalized location, It includes the position and orientation of the end point in the world coordinate system; These correspond to the state variables of the entire robot, the state variables of the torso, and the first... The state variables of the leg and the state variables of the working arm; Indicates the first Forward kinematics of a leg in the torso coordinate system; This represents the forward kinematics of the working arm in the torso coordinate system; This represents the transformation matrix from the torso coordinate system to the world coordinate system; The robot's gait is described using a continuous time variable. The robot's motion is decomposed into trunk center of mass motion, leg motion, and working arm motion. The motion curves of each motion are described, and the constraints on the robot's motion are constructed. The time variable is the robot phase duration. Based on the robot's current state and the set expected task objectives, a nonlinear optimization problem for the robot's whole-body motion trajectory is established by combining the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints on the robot's motion. The optimal motion trajectory is obtained by using an optimization solution library.

2. The method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot as described in claim 1, characterized in that, The dynamic model of the robot's torso center of mass is represented as follows: In the above formula, This represents the robot's torso weight. Represents gravitational acceleration. This represents the linear acceleration at the center of mass. For time variables, Let be the angular velocity of the center of mass. Represents angular acceleration. The inertial parameters representing the torso, Indicates the first The equivalent force at the torso's center of mass corresponding to the end of the arm originates from the force exerted by the supporting leg on the ground and the interaction force between the robotic arm's end and the work object. With the corresponding lever arm The product of represents the equivalent torque. Indicates the first The end is in t The location at any given moment.

3. The method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot as described in claim 1, characterized in that, The robot's motion is decomposed into trunk center of mass motion, leg motion, and working arm motion. Among them, the leg motion is further subdivided into supporting leg motion and swinging leg motion. The motion curves for each motion are described as follows: the fourth motion curve of the trunk's center of mass, the equation of the fixed state of the supporting leg, the third motion curve of the swinging leg under force, and the third motion curve of the working arm.

4. The method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot as described in claim 1, characterized in that, The constraints include: contact constraints, non-contact constraints, kinematic constraints, terrain constraints, and phase-time constraints.

5. The method for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot as described in claim 4, characterized in that, The contact constraints include force constraints and friction cone constraints, which are expressed as follows: in, Indicates the first Each foot tip x , y Positions in two directions, This represents the thrust vector generated by the foot on the ground. Represents the terrain surface The direction vector at the location, Gravity represents the force related to the robot's mass. A scalar quantity representing thrust. Indicates the first One leg at a time point Is it in a support phase? Indicates the two tangent directions. The coefficient of friction; The kinematic constraints include those for the limbs and the working arm. The kinematic constraints for the limbs are defined as follows: Each leg does not exceed the range of the cube corresponding to the current index. in, Represents the rotation matrix from the world coordinate system to the torso coordinate system; Indicates the first The end is in t The position at that moment; Indicates the first The joint vector of a leg, and These represent the upper and lower limits for each joint, respectively. This represents the transformation matrix from the torso coordinate system to the world coordinate system; The kinematic constraints of the working arm are expressed as follows: in, This indicates the position of the end effector arm relative to the world coordinate system. This indicates the reference point of the working arm in the workspace, with the reference coordinate axes parallel to the coordinate axes of the world coordinate system; The unit direction vector representing the world coordinate system; For one The row vectors contain the dimension values ​​of the cube constraints; The terrain constraints are expressed as follows: in, Indicates the first Each foot tip z The position of direction, Indicates the first Each foot tip x , y Topographic information indicating the location in a given direction; The phase-time constraint is expressed as: in, For time variables, , The total time for an entire gait.

6. A system for optimizing the whole-body motion trajectory of a quadrupedal single-arm robot, characterized in that, include: The modeling module is used to create kinematic models of the robot's limbs and working arm, as well as a dynamic model of the torso's center of mass, for a quadrupedal single-arm robot. The forward kinematic models of the robot's limbs and working arm are represented as follows: in, Indicates the first The position of each end in the world coordinate system; It represents the feet of four legs. Indicates the end of the working arm; The dimension representing the end-effector pose, when using linear position, When using generalized location, It includes the position and orientation of the end point in the world coordinate system; These correspond to the state variables of the entire robot, the state variables of the torso, and the first... The state variables of the leg and the state variables of the working arm; Indicates the first Forward kinematics of a leg in the torso coordinate system; This represents the forward kinematics of the working arm in the torso coordinate system; This represents the transformation matrix from the torso coordinate system to the world coordinate system; The motion analysis module is used to describe the robot's gait using continuous time variables. It decomposes the robot's motion into trunk center of mass motion, leg motion, and working arm motion, describes the motion curves of each motion, and constructs the constraints on the robot during its motion. The time variable is the robot phase duration. The optimal motion trajectory generation module is used to establish a nonlinear optimization problem of the robot's whole-body motion trajectory based on the robot's current state and the set expected task objective, by combining the kinematic model, dynamic model, gait, motion curves of each decomposed motion, and constraints of the robot's motion. The optimal motion trajectory is obtained by solving the problem using an optimization solution library.

7. An electronic device, characterized in that, include: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the whole-body motion trajectory optimization method for a quadrupedal single-arm robot as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The device stores executable instructions that, when executed by a processor, implement the whole-body motion trajectory optimization method for a quadrupedal single-arm robot as described in any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes executable instructions stored in a computer-readable storage medium; When the processor of the electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, it implements the whole-body motion trajectory optimization method for a quadrupedal single-arm robot as described in any one of claims 1-5.

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