Robot parameter optimization, calibration method, device, system, robot and medium

Abstract

The present application relates to a robot parameter optimization and calibration method, device, system, robot and medium, the method comprising: obtaining the robot's screw kinematic model, and obtaining the functional relationship between the positioning error of the robot's mechanical arm and the robot's parameter error based on the screw kinematic model; obtaining the robot's mechanical arm's distance error model, and calculating the parameter error of the robot's terminal real-time positioning based on the functional relationship and the distance error model; optimizing the robot's kinematic parameters corresponding to the real-time positioning instruction obtained by the robot based on the parameter error. The present application can optimize the robot's positioning parameters efficiently and accurately without additional measuring instruments, improve the efficiency and accuracy of the robot calibration, and meet the working requirements of the surgical site environment.

Description

Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a robot parameter optimization, calibration method, device, system, robot and medium. Background Art

[0002] With the rapid development of robotics technology, the roles played by various robots in people's work and life are becoming increasingly important. For example, medical robotic arms have gradually become one of the effective solutions for surgical robot systems, and their positioning accuracy directly affects the safety and reliability of the operation.

[0003] However, the positioning accuracy of the robot arm is affected by factors such as processing and assembly, which restricts the accuracy, efficiency and safety of the robot arm positioning. If the calibration model is established through position error, the coordinate system error between the measurement system coordinate system and the robot arm coordinate system will be introduced during the actual calibration process, resulting in the coupling of the coordinate system error with the robot arm joint parameter error, affecting the effectiveness of the robot calibration result.

[0004] In addition, traditional robot arm positioning error compensation technology mainly relies on external measurement equipment, such as laser trackers or wire sensors, etc., which not only has high technical implementation costs, but also requires the measurement equipment to be preheated and wait for a period of time before use so that the electronic components inside the measurement equipment can reach thermal stability equilibrium, resulting in a long time and low efficiency for the error compensation technology to be implemented, making it difficult to meet the application requirements of the surgical environment. In addition, it is difficult for external measurement equipment to obtain actual positioning errors in measurement environments with factors such as occlusion or reflection, and the scope of application is limited. Summary of the invention

[0005] Based on this, it is necessary to provide a robot parameter optimization and calibration method, device, system, robot and medium to address the technical problems in the above-mentioned background technology, so as to optimize the robot positioning parameters efficiently and accurately without additional measuring instruments, so as to improve the efficiency and accuracy of robot calibration and meet the working requirements of the surgical site environment.

[0006] To achieve the above objectives and other objectives, the first aspect of the present application provides a robot parameter optimization method, comprising:

[0007] Obtaining a screw kinematics model of the robot, and obtaining a functional relationship between a positioning error of the robot arm and a parameter error of the robot according to the screw kinematics model;

[0008] Obtaining a distance error model of the robot manipulator, and calculating a parameter error of real-time positioning of the robot end according to the functional relationship and the distance error model;

[0009] The robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot are optimized according to the parameter error of the real-time positioning of the robot end.

[0010] In the robot parameter optimization method in the above embodiment, after obtaining the screw kinematic model, the robot is set to obtain the functional relationship between the positioning error of the robot mechanical arm and the parameter error of the robot according to the screw kinematic model, so that after obtaining the distance error model of the robot mechanical arm, the robot can calculate the kinematic parameter error of the robot according to the functional relationship and the distance error model, and optimize the robot kinematic parameters in a numerical optimization manner, so as to improve the robot positioning accuracy by compensating the joint angle based on the obtained optimized kinematic parameters, thereby improving the efficiency and accuracy of robot calibration. Since the present application establishes the screw kinematic model of the robot based on the screw theory without additional measuring instruments, it can meet the requirements of the robot kinematic parameters for the completeness of the posture error and improve the accuracy of the error model. Since the present application uses the distance error model of the robot arm to calculate the parameter error of the real-time positioning of the robot end, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0011] In one embodiment, the step of calculating the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model includes:

[0012] Obtaining the real-time positioning instruction, wherein the real-time positioning instruction is used to control the end of the robot to reach a preset measurement point;

[0013] Obtaining the posture coordinates and a set of joint angles corresponding to the real-time positioning instruction when the robot end reaches any of the preset measurement points;

[0014] The posture coordinates and a set of joint angles corresponding to each of the preset measurement points are input into the functional relationship and the distance error model to calculate the parameter error of the real-time positioning of the robot end.

[0015] In one embodiment, the step of optimizing the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error includes:

[0016] Obtaining robot kinematic parameters corresponding to the real-time positioning instruction;

[0017] Calculating a distance error vector according to the robot kinematic parameters;

[0018] Calculating a distance error Jacobian matrix, and calculating a real-time distance error according to the distance error vector, the distance error Jacobian matrix and the distance error model;

[0019] Determine whether the real-time distance error is greater than or equal to a preset error threshold;

[0020] If so, a first preset algorithm is used to calculate the kinematic parameter error of the robot, and corresponding kinematic parameters are updated according to the kinematic parameter error, so as to calculate the real-time distance error according to the updated kinematic parameters;

[0021] Otherwise, the kinematic parameters are output.

[0022] In one embodiment, the robot kinematic parameters include joint parameters and / or zero position parameters.

[0023] In one embodiment, the joint parameters include at least one of a joint angle, a joint rotation, a joint offset, and a joint rotation.

[0024] A second aspect of the present application provides a robot parameter calibration method, comprising:

[0025] Obtaining a real-time positioning instruction, wherein the real-time positioning instruction is used to control a positioning terminal at the end of the robot to reach a preset measurement point;

[0026] Acquire kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point;

[0027] According to the kinematic parameters and the posture coordinates, the kinematic parameters are optimized using the robot parameter optimization method described in any of the embodiments of the present application, and the optimized kinematic parameters are obtained;

[0028] The robot is calibrated according to the optimized kinematic parameters.

[0029] In the robot parameter calibration method in the above embodiment, after obtaining the screw kinematic model, the robot is set to obtain the functional relationship between the positioning error of the robot mechanical arm and the parameter error of the robot according to the screw kinematic model, so that after obtaining the distance error model of the robot mechanical arm, the robot can calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model, optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, and calibrate the robot based on the obtained optimized kinematic parameters to improve the efficiency and accuracy of robot calibration. Since the present application establishes the screw kinematic model of the robot based on the screw theory without additional measuring instruments, it can meet the requirements of the robot connecting rod for the completeness of the posture error and improve the accuracy of the error model. Since the present application adopts the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot terminal, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0030] In one embodiment, the step of calibrating the robot according to the optimized kinematic parameters comprises:

[0031] Analyzing the kinematic parameters and obtaining the joint angles;

[0032] Establishing a preset mathematical model according to the joint angle;

[0033] Calculating the error transfer matrix of the joint angle, and calculating the posture error according to the error transfer matrix and the preset mathematical model;

[0034] Determining whether the posture error is greater than or equal to a preset accuracy threshold;

[0035] If yes, a second preset algorithm is used to calculate the joint angle error of the robot, and the corresponding joint angle is updated according to the joint angle error, so as to calculate the posture error according to the updated joint angle;

[0036] Otherwise, the robot is calibrated according to the joint angles.

[0037] A third aspect of the present application provides a robot parameter optimization device, comprising:

[0038] A parameter error function acquisition module, used to acquire a screw kinematic model of the robot, and acquire a functional relationship between a positioning error of the robot manipulator and a parameter error of the robot according to the screw kinematic model;

[0039] A parameter error calculation module is used to obtain a distance error model of the robot manipulator, and calculate the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model;

[0040] The parameter optimization module is used to optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, and obtain the optimized kinematic parameters.

[0041] In the robot parameter optimization device in the above embodiment, the parameter error function acquisition module is used to acquire the robot's screw kinematic model, and the parameter error calculation module is used to acquire the functional relationship between the positioning error of the robot mechanical arm and the robot's parameter error according to the screw kinematic model, so that after the parameter optimization module acquires the distance error model of the robot mechanical arm, it can calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model, so as to optimize the robot kinematic parameters corresponding to the real-time positioning instruction acquired by the robot according to the parameter error. Thus, the robot can be calibrated according to the acquired optimized kinematic parameters, and the efficiency and accuracy of robot calibration can be improved. Since the present application establishes the screw kinematic model of the robot based on the screw theory without additional measuring instruments, it can meet the requirements of the robot link for the completeness of the posture error and improve the accuracy of the error model. Since the present application uses the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot terminal, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0042] A fourth aspect of the present application provides a robot parameter calibration device, comprising:

[0043] A positioning instruction acquisition module is used to acquire real-time positioning instructions, wherein the instructions are used to control the positioning terminal at the end of the robot to reach a preset measurement point;

[0044] A calibration data acquisition module, used to obtain kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point;

[0045] A robot parameter optimization device as described in any of the embodiments of the present application, used to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain optimized kinematic parameters;

[0046] A calibration module is used to calibrate the robot according to the optimized kinematic parameters.

[0047] In the robot parameter calibration device in the above embodiment, the real-time positioning instruction is obtained through the positioning instruction acquisition module, wherein the instruction is used to control the positioning terminal at the end of the robot to reach the preset measurement point; the kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches the preset measurement point are obtained based on the calibration data acquisition module; the robot number optimization device as described in any embodiment of the present application is used to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain the optimized kinematic parameters; so that the calibration module can calibrate the robot according to the optimized kinematic parameters, thereby improving the efficiency and accuracy of robot calibration. Since the present application establishes the robot's spinor kinematic model based on the spinor theory without additional measuring instruments, it can meet the robot connecting rod's requirements for the completeness of posture errors and improve the accuracy of the error model. Since the present application uses the distance error model of the robotic arm to calculate the parameter error of the real-time positioning of the robot end, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0048] A fifth aspect of the present application provides a robot parameter calibration system, comprising:

[0049] A calibration fixture, on which a plurality of preset measuring points are arranged;

[0050] An end device is arranged at the end of the robot, and a positioning terminal is arranged at one end of the end device away from the end of the robot;

[0051] A robot parameter optimization device or a robot parameter calibration device as described in any of the embodiments of the present application is used to obtain the kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point, and to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and to obtain the optimized kinematic parameters.

[0052] In one of the embodiments, a plurality of groove-shaped measuring points are arranged on the surface of the calibration tooling close to the positioning terminal, and the end of the positioning terminal away from the end of the robot is spherical, so that when the positioning terminal is located inside the groove-shaped measuring point, the kinematic parameters corresponding to the real-time positioning instruction and the posture coordinates of the preset measurement point can be obtained, thereby improving the efficiency of obtaining the calibration sampling data.

[0053] In one of the embodiments, the shape of the groove-shaped measuring point matches the shape of the positioning terminal, and the volume of the groove-shaped measuring point matches the volume of the positioning terminal, so as to improve the accuracy of obtaining calibration sampling data.

[0054] The sixth aspect of the present application provides a robot, comprising a robot body, a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the steps of any method described in any embodiment of the present application when executing the computer program.

[0055] The seventh aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any embodiment of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 A schematic diagram of a flow chart of a robot parameter optimization method provided in one embodiment of the present application;

[0058] Figure 2 A schematic flow chart of a robot parameter optimization method provided in another embodiment of the present application;

[0059] Figure 3 A schematic flow chart of a robot parameter optimization method provided in another embodiment of the present application;

[0060] Figure 4 A schematic diagram of a flow chart of a robot parameter calibration method provided in one embodiment of the present application;

[0061] Figure 5 A schematic flow chart of a robot parameter calibration method provided in another embodiment of the present application;

[0062] Figure 6 This is a schematic diagram of the structure of a robot parameter optimization device provided in one embodiment of the present application;

[0063] Figure 7 This is a schematic diagram of the structure of a robot parameter calibration device provided in one embodiment of the present application;

[0064] Figure 8 A schematic diagram of the structure of a robot parameter calibration system provided in one embodiment of the present application;

[0065] Figure 9a This is a schematic diagram of the structure of a robot provided in one embodiment of the present application;

[0066] Figure 9bA schematic diagram of an application scenario of a robot parameter calibration system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present application are provided in the drawings. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive.

[0068] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0069] In the case of using “including”, “having”, and “comprising” described herein, another component may be added unless a clear limiting term such as “only”, “consisting of”, etc. is used. Unless mentioned otherwise, a term in the singular form may include a plural form and should not be understood as being one in number.

[0070] It should be understood that although the terms "first", "second", etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element without departing from the scope of the present application.

[0071] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0072] Since traditional robot arm calibration has low efficiency and low positioning accuracy, the implementation cost is high and it is difficult to meet the requirements of surgical robot arms for calibration efficiency and positioning accuracy, there is an urgent need to provide a method that can effectively improve the calibration efficiency and positioning accuracy of the robot arm.

[0073] One of the key steps to achieve robot arm calibration is to establish an error model of the robot arm. In the prior art, the relationship model between the robot arm link size error and the end positioning error is mainly established based on the Denavit-Hartenberg (DH) model. This modeling method has at least two defects: (1) The error model requires completeness, and the DH model uses 4 or 5 parameters and is essentially unable to fully express the error characteristics between the links; (2) The DH model is a model based on position error. In the actual calibration process, the error between the measurement system coordinate system and the robot arm coordinate system will be introduced. The error of this coordinate system is coupled with the size error of the robot arm end link, affecting the calibration accuracy of the robot.

[0074] In terms of calibration test design methods, existing technologies are mainly based on external measurement equipment, which has high implementation costs and requires preheating and waiting before use, resulting in long calibration experiment time, low efficiency, and failure to meet the application requirements of surgical site environments. In terms of error prediction and compensation, existing technologies are mainly based on external measurement equipment such as cameras and laser trackers to obtain the actual positioning error of the end of the robotic arm. The cost of online error acquisition is high, and it is easily affected by factors such as occlusion or reflection, and its scope of application is limited.

[0075] The present application aims to obtain a method for identifying and optimizing robot parameters based on screw theory and distance measurement, so as to improve the efficiency of robot arm calibration and the accuracy of positioning.

[0076] Please refer to Figure 1 In one embodiment of the present application, a robot parameter optimization method is provided, comprising:

[0077] Step 22, obtaining a screw kinematics model of the robot, and obtaining a functional relationship between a positioning error of the robot manipulator and a parameter error of the robot according to the screw kinematics model;

[0078] Step 24, obtaining a distance error model of the robot manipulator, and calculating a parameter error of real-time positioning of the robot end according to the functional relationship and the distance error model;

[0079] Step 26, optimizing the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error of the real-time positioning of the robot end.

[0080] As an example, please refer to Figure 1 First, we can obtain the base coordinate system Base of the robot and the end coordinate system E of the robot end, and calculate the pose matrix of the end coordinate system of the robot end relative to the base coordinate system of the robot. For example, when the robot is in the zero position state, the pose matrix of the end coordinate system E of the robot end relative to the base coordinate system is P E0 , where PE0 The pose matrix of the robot end when it is zero position. Then, the robot's screw kinematic model is established according to the pose matrix. After obtaining the screw kinematic model, the robot obtains the functional relationship between the positioning error of the robot mechanical arm and the parameter error of the robot according to the screw kinematic model, so that after obtaining the distance error model of the robot mechanical arm, the robot can calculate the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model, so as to optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, so as to calibrate the robot based on the obtained optimized kinematic parameters, thereby improving the efficiency and accuracy of robot calibration. Since the present application establishes the robot's screw kinematic model based on the screw theory without additional measuring instruments, it can meet the requirements of the robot connecting rod for the completeness of the pose error and improve the accuracy of the error model. Since the present application adopts the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot end, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0081] As an example, please refer to Figure 1 In one embodiment of the present application, the step of obtaining a functional relationship between a positioning error of a robot manipulator and a parameter error of the robot according to the screw kinematic model comprises:

[0082] The functional relationship between the positioning error of the robotic arm and the parameter error of the robot is calculated according to the following formula:

[0083] δP E =J e ·δe;

[0084]

[0085]

[0086]

[0087] In the above formula, exp is the exponential with base e, θ m is the joint angle of the robot’s mth joint, p E0 is the pose matrix of the origin of the robot end effector coordinate system relative to the robot base coordinate system, that is, the pose matrix of the robot end at zero position, R E0 The pose matrix of the robot end effector relative to the robot base coordinate system when is zero position, is the joint rotation of the robot’s mth joint, P E is the screw kinematic model of the robot, δP E PE The partial derivative of and is the error between the robot’s command position and the actual position, J e is the error transfer matrix corresponding to the robot error source parameters, δe is the vector composed of the robot parameter errors, n is the number of robot joints, and m and n are both positive integers. Substituting into the Products of exponentials (POE) formula, we can get the robot's screw kinematic model P E .

[0088] As an example, please refer to Figure 1 In one embodiment of the present application, the step of obtaining the distance error model of the robot manipulator includes:

[0089] The difference Δl(i,j) between the actual distance and the command distance between the i-th point and the j-th point of the real-time positioning of the robot end is calculated according to the following formula:

[0090]

[0091] Among them, x r (j), y r (j), z r (j) represents the actual position coordinates of the jth point of the robot in its base coordinate system, x r (i) y r (i) z r (i) represents the actual position coordinates of the robot's i-th point in its base coordinate system, l r (i, j) represents the actual distance between the i-th point and the j-th point in the robot's terminal coordinate system. The i-th point and the j-th point are arbitrary points of the robot in three-dimensional space, and Δl(i, j) is the actual distance error, which can be measured and obtained. e (j) is the error transfer matrix corresponding to the j-th point (joint angle), J e (i) is the error transfer matrix corresponding to the i-th point (joint angle).

[0092] For further information, please refer to Figure 2 In one embodiment of the present application, the step of calculating the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model includes:

[0093] Step 242, obtaining the real-time positioning instruction, wherein the real-time positioning instruction is used to control the robot end to reach a preset measurement point;

[0094] Step 244, obtaining the posture coordinates and a set of joint angles corresponding to the real-time positioning instruction when the robot end reaches any of the preset measurement points;

[0095] Step 246, inputting the posture coordinates and a set of joint angles corresponding to each of the preset measurement points into the functional relationship and the distance error model to calculate the parameter error of the real-time positioning of the robot end.

[0096] As an example, please refer to Figure 2 , a preset measurement point with known posture coordinates can be selected in the robot workspace. When the robot controls its terminal to reach the preset measurement point based on the acquired real-time positioning instruction, the corresponding posture coordinates and a set of joint angles are acquired and saved. Since the actual posture coordinates of the preset measurement point are known, the posture coordinates and a set of joint angles corresponding to each of the preset measurement points are input into the functional relationship and the distance error model, and the parameter error of the real-time positioning of the robot terminal can be calculated.

[0097] For further information, please refer to Figure 3 In one embodiment of the present application, the step of optimizing the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error includes:

[0098] Step 261, obtaining robot kinematic parameters corresponding to the real-time positioning instruction;

[0099] Step 262, calculating a distance error vector according to the robot kinematic parameters;

[0100] Step 263, calculating the distance error Jacobian matrix, and calculating the real-time distance error according to the distance error vector, the distance error Jacobian matrix and the distance error model;

[0101] Step 264, determining whether the real-time distance error is greater than or equal to a preset error threshold;

[0102] Step 265: If yes, a first preset algorithm is used to calculate the kinematic parameter error of the robot, and corresponding kinematic parameters are updated according to the kinematic parameter error, so as to calculate the real-time distance error according to the updated kinematic parameters;

[0103] Step 266: Otherwise, the kinematic parameters are output.

[0104] As an example, please refer to Figure 3, the Newton method can be used to compensate the kinematic parameters of the robot in real time, so that the real-time distance error of the robot positioning meets the preset error threshold requirement. The first preset algorithm can be set to include at least one of the Levenberg-Marquadt algorithm (Levenberg-Marquadt, LM), the least squares algorithm and the particle swarm algorithm. In order to avoid the problem of non-convergence or local optimal reduction due to large errors in the process of using the preset mathematical model, one or more of the LM algorithm, the least squares algorithm or the particle swarm algorithm can be used to compensate for the kinematic parameters measured in real time and obtain the optimized kinematic parameters. Under the premise of no additional measuring instruments, the robot positioning parameters can be optimized efficiently and with high precision, which can effectively improve the efficiency and accuracy of robot calibration and meet the working requirements of the surgical site environment.

[0105] In one embodiment of the present application, the robot kinematic parameters include joint parameters and / or zero position parameters, wherein the joint parameters may include joint angles and / or joint rotations.

[0106] For further information, please refer to Figure 4 In one embodiment of the present application, a robot parameter calibration method is provided, comprising:

[0107] Step 32, obtaining a real-time positioning instruction, wherein the real-time positioning instruction is used to control the positioning terminal at the end of the robot to reach a preset measurement point;

[0108] Step 34, obtaining kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point;

[0109] Step 36, according to the kinematic parameters and the posture coordinates, the robot parameter optimization method described in any embodiment of the present application is used to optimize the kinematic parameters and obtain optimized kinematic parameters;

[0110] Step 38, calibrating the robot according to the optimized kinematic parameters.

[0111] As an example, please refer to Figure 4, after the robot obtains the screw kinematic model, it is set to obtain the functional relationship between the positioning error of the robot mechanical arm and the parameter error of the robot according to the screw kinematic model, so that after the robot obtains the distance error model of the robot mechanical arm, it can calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model, optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, and calibrate the robot based on the obtained optimized kinematic parameters to improve the efficiency and accuracy of robot calibration. Since the present application establishes the screw kinematic model of the robot based on the screw theory without additional measuring instruments, it can meet the requirements of the robot connecting rod for the completeness of the posture error and improve the accuracy of the error model. Since the present application adopts the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot terminal, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0112] For further information, please refer to Figure 5 In one embodiment of the present application, the step of calibrating the robot according to the optimized kinematic parameters comprises:

[0113] Step 381, analyzing the kinematic parameters and obtaining the joint angles;

[0114] Step 382, ​​establishing a preset mathematical model according to the joint angle;

[0115] Step 383, calculating the error transfer matrix of the joint angle, and calculating the posture error according to the error transfer matrix and the preset mathematical model;

[0116] Step 384, determining whether the posture error is greater than or equal to a preset accuracy threshold;

[0117] Step 385, if yes, then use a second preset algorithm to calculate the joint angle error of the robot, and update the corresponding joint angle according to the joint angle error, so as to calculate the posture error according to the updated joint angle;

[0118] Step 386, conversely, calibrate the robot according to the joint angles.

[0119] As an example, please refer to Figure 5The preset mathematical model can be set as the Newton method model, and the Newton method is used to compensate the joint angle of the robot in real time, so that the position error of the robot's mechanical arm terminal positioning meets the preset accuracy threshold requirement. The second preset algorithm can be set to include at least one of the LM algorithm, the least squares algorithm and the particle swarm algorithm, which compensates the joint angle of the robot in real time, and effectively improves the accuracy of the robot's mechanical arm terminal positioning without additional measuring instruments.

[0120] For further information, please refer to Figure 6 In one embodiment of the present application, a robot parameter optimization device 100 is provided, including a parameter error function acquisition module 102, a parameter error calculation module 104 and a parameter optimization module 106; the parameter error function acquisition module 102 is used to obtain the robot's screw kinematic model, and obtain the functional relationship between the positioning error of the robot's mechanical arm and the robot's parameter error according to the screw kinematic model; the parameter error calculation module 104 is used to obtain the distance error model of the robot's mechanical arm, and calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model; the parameter optimization module 106 is used to optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, and obtain the optimized kinematic parameters.

[0121] As an example, please refer to Figure 6 , the parameter error function acquisition module 102 is used to acquire the robot's screw kinematic model, and the parameter error calculation module 104 is used to acquire the functional relationship between the positioning error of the robot's mechanical arm and the robot's parameter error according to the screw kinematic model, so that the parameter optimization module 106 can calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model after acquiring the distance error model of the robot's mechanical arm, so as to optimize the robot kinematic parameters corresponding to the real-time positioning instruction acquired by the robot according to the parameter error. Thus, the robot can be calibrated according to the obtained optimized kinematic parameters, and the efficiency and accuracy of the robot calibration can be improved. Since the present application establishes the robot's screw kinematic model based on the screw theory without additional measuring instruments, it can meet the requirements of the robot link for the completeness of the posture error and improve the accuracy of the error model. Since the present application uses the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot terminal, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0122] For further information, please refer to Figure 7In one embodiment of the present application, a robot parameter calibration device 200 is provided, including a positioning instruction acquisition module 201, a calibration data acquisition module 202, a robot parameter optimization device 100 as described in any embodiment of the present application, and a calibration module 206, wherein the positioning instruction acquisition module 201 is used to acquire real-time positioning instructions, wherein the instructions are used to control the positioning terminal at the end of the robot to reach a preset measurement point; the calibration data acquisition module 202 is used to acquire the kinematic parameters and posture coordinates corresponding to the real-time positioning instructions when the positioning terminal reaches the preset measurement point; the robot parameter optimization device 100 is used to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain the optimized kinematic parameters; the calibration module 206 is used to calibrate the robot according to the optimized kinematic parameters.

[0123] As an example, please refer to Figure 7 , obtain the real-time positioning instruction through the positioning instruction acquisition module 201, wherein the instruction is used to control the positioning terminal at the end of the robot to reach the preset measurement point; based on the calibration data acquisition module 202, obtain the kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches the preset measurement point; use the robot data optimization device 100 as described in any embodiment of the present application, optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain the optimized kinematic parameters; so that the calibration module 206 can calibrate the robot according to the optimized kinematic parameters, and improve the efficiency and accuracy of robot calibration. Since the present application establishes the robot's spinor kinematic model based on the spinor theory without additional measuring instruments, it can meet the robot connecting rod's requirements for the completeness of posture errors and improve the accuracy of the error model. Since the present application uses the distance error model of the robotic arm to calculate the parameter error of the real-time positioning of the robot end, it does not rely on the measurement system coordinate system, reduces the influence of the coordinate system conversion error, effectively improves the robot's calibration accuracy, and can meet the working requirements of the surgical site environment.

[0124] For further information, please refer to Figure 8In one embodiment of the present application, a robot parameter calibration system is provided, including an end device 2, a calibration tool 3, and a robot parameter optimization device 100 or a robot parameter calibration device 200 as described in any embodiment of the present application, wherein a plurality of preset measurement points 31 are arranged on the calibration tool 3; the end device 2 is arranged at the end of the robot 1, and a positioning terminal 210 is arranged at the end of the end device 2 away from the end of the robot; the robot parameter optimization device 100 or the robot parameter calibration device 200 can obtain the kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal 210 reaches the preset measurement point 31, optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain the optimized kinematic parameters.

[0125] As an example, please refer to Figure 8 , by setting a plurality of preset measurement points 31 with known posture coordinates on the calibration tool 3, setting an end instrument 2 at the end of the robot, and setting a positioning terminal 210 at the end of the end instrument 2 away from the end of the robot, so as to obtain the kinematic parameters corresponding to the real-time positioning instruction and the posture coordinates of the preset measurement point when the positioning terminal 210 contacts the preset measurement point 31, and optimizing the kinematic parameters in a numerical optimization manner to obtain optimized kinematic parameters, so as to improve the robot calibration by compensating the joint angle based on the optimized kinematic parameters, thereby improving the efficiency and accuracy of the robot calibration. Since the present application establishes the robot's spinor kinematic model based on the spinor theory without additional measuring instruments, it can meet the requirements of the robot's connecting rod for the completeness of posture errors and improve the accuracy of the error model. Since the present application adopts the distance error model of the robotic arm to calculate the parameter error of the real-time positioning of the robot end, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment. Since the calibration tooling and end-device involved in this embodiment have low implementation cost and simple implementation method, the cost and complexity of robot parameter calibration are effectively reduced.

[0126] Figure 8 The robot base coordinate system Oxyz and the robot end effector coordinate system O'x'y'z' illustrated in the figure are intended to assist in schematically illustrating the implementation principle of the present application. In other embodiments of the present application, different robot base coordinate systems or different robot end effector coordinate systems may also be set.

[0127] As an example, please refer to Figure 8In one embodiment of the present application, a plurality of measuring points 31 are provided on a surface 3a of the calibration tool 3 close to the positioning terminal 210. The measuring point 31 is in a groove shape, and the end of the positioning terminal 210 away from the end of the robot is in a spherical shape, so that when the positioning terminal 210 is located inside the measuring point 31, the kinematic parameters corresponding to the real-time positioning instruction and the posture coordinates of the preset measuring point can be obtained, thereby improving the efficiency of obtaining the calibration sampling data.

[0128] As an example, please refer to Figure 8 In one embodiment of the present application, the shape of the groove-shaped measuring point 31 matches the shape of the positioning terminal 210, and the volume of the groove-shaped measuring point 31 matches the volume of the positioning terminal 210 to improve the accuracy of obtaining calibration sampling data.

[0129] As an example, see Figure 9a and Figure 9b In one embodiment of the present application, the robot includes a robot arm body 11, a first joint 12, a second joint 13, a third joint 14, a fourth joint 15 and a fifth joint 16, the free end of the fifth joint 16 is provided with an end tool 2, and the end tool 2 is provided with a positioning terminal 210 at one end away from the end of the robot; the surface 3a of the calibration tool 3 close to the positioning terminal 210 is provided with a first measuring point 3A, a second measuring point 3B, a third measuring point 3C, a fourth measuring point 3D and a fifth measuring point 3E, and the first measuring point 3A, the second measuring point 3B, the third measuring point 3C, and the fourth measuring point 3D can be set symmetrically with the fifth measuring point 3E as the center point, so as to determine the posture coordinates of the five measuring points.

[0130] As an example, please refer to Figure 9a and Figure 9b, according to the ISO repeatability positioning accuracy evaluation standard, the working space of the robot arm can be determined, and the repeatability positioning accuracy of 5 points in the working space can be evaluated. If the repeatability positioning accuracy is not good, check the problems in the mechanical structure assembly; if the positioning accuracy meets the preset accuracy requirements, proceed to the next step of calibration. The calibration fixture 3 can be fixed on a movable workbench in the robot workspace, and the posture of the calibration fixture 3 can be adjusted to ensure that the positioning terminal 210 at the end of the robot arm can reach the 5 measurement points on the calibration fixture 3. 10 sets of relatively dispersed fixture postures are selected, and the posture coordinates of the corresponding measurement points are determined. Then, the robot arm is dragged by dragging teaching mode to make the end positioning terminal 210 reach the preset measurement point. For example, the robot is controlled to drive the positioning terminal 210 to contact the 5 measurement points on the tooling in turn, and the joint angle when the positioning terminal 210 contacts the first measurement point 3A and the second measurement point 3B on the calibration tooling 3, as well as the nominal distance between the first measurement point 3A and the second measurement point 3B, are obtained and saved, and the two joint angles and the nominal distance between the two points are obtained as a set of measurement data. Similarly, the two joint angles and the nominal distance between the two points corresponding to the second measurement point 3B and the third measurement point 3C are obtained respectively, the two joint angles and the nominal distance between the two points corresponding to the third measurement point 3C and the fourth measurement point 3D are obtained, the two joint angles and the nominal distance between the two points corresponding to the fourth measurement point 3D and the fifth measurement point 3E are obtained, and the two joint angles and the nominal distance between the two points corresponding to the fifth measurement point 3E and the first measurement point 3A are obtained. The posture of the calibration tooling 3 is changed, and the above data collection work is repeated to obtain 50 sets of measurement data. Then, the functional relationship between the positioning error of the manipulator and the parameter error of the robot can be calculated according to the following formula:

[0131] δP E =J e ·δe;

[0132]

[0133]

[0134]

[0135] In the above formula, exp is the exponential with base e, θ t is the joint angle of the robot's t joint, p E0 is the pose matrix of the origin of the robot end effector coordinate system relative to the robot base coordinate system, that is, the pose matrix of the robot end at zero position, R E0 The posture matrix of the robot end effector relative to the robot base coordinate system when is zero position, is the joint rotation of the robot's t joint, δP E P EThe partial derivative of and is the error between the robot’s command position and the actual position, J e is the error transfer matrix corresponding to the robot error source parameters, J ξ P E The matrix composed of partial derivatives of the motion spinor, J P0 P E The matrix composed of the partial derivatives of the zero-position parameters, δe is the vector composed of the parameter errors of the robot, t is a positive integer. Substituting into the exponential product formula (Product of Experts, POE) formula, we can get the robot's screw kinematic model P E , is the error of the joint rotation parameter, δP E0 Represents the error of the robot's zero-position parameter. Then, the difference Δl(i,j) between the actual distance and the command distance between the i-th point and the j-th point of the robot positioning is calculated according to the following formula:

[0136]

[0137] Among them, x r (j), y r (j), z r (j) represents the actual position coordinates of the jth point of the robot in its base coordinate system, x r (i) y r (i) z r (i) represents the actual position coordinates of the robot's i-th point in its base coordinate system, l r (i, j) represents the actual distance between the i-th point and the j-th point in the robot's terminal coordinate system. The i-th point and the j-th point are arbitrary points of the robot in three-dimensional space, and Δl(i, j) is the actual distance error, which can be measured and obtained. e (j) is the error transfer matrix corresponding to the j-th point (joint angle), J e (i) is the error transfer matrix corresponding to the i-th point (joint angle).

[0138] The first 30 sets of measurement data are input into the distance error model for parameter identification and calibration. If the maximum value of the distance error of the robot positioning meets the preset error threshold requirement or the number of cycles exceeds the maximum number of iterations, the robot kinematic parameters such as joint angle, joint rotation angle and joint offset are obtained. The last 20 sets of measurement data are used to evaluate the distance error and positioning accuracy of the calibrated robot arm. If the distance error and positioning accuracy obtained each time meet the corresponding requirements after repeated measurements, it means that the calibration result is valid and can be updated to the robot controller.

[0139] Since the inverse kinematics solution is used in the above embodiment, the obtained joint angle is not actually at the target posture. In order to make the end of the robot arm closer to the target posture, the Newton method can be used to compensate the joint angle of the robot in real time, so that the posture error of the robot arm end positioning meets the preset accuracy threshold requirement. Since this embodiment uses an algorithm to compensate the joint angle of the robot in real time, without the need for additional measuring instruments, the accuracy of the robot arm end positioning is effectively improved.

[0140] Furthermore, in one embodiment of the present application, a robot is provided, comprising a robot body, a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the steps of any method described in the embodiments of the present application when executing the computer program.

[0141] Furthermore, in one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any embodiment of the present application are implemented.

[0142] In the robot or computer-readable storage medium in the above embodiment, after obtaining the screw kinematic model, the robot is set to obtain the functional relationship between the positioning error of the robot mechanical arm and the parameter error of the robot according to the screw kinematic model, so that after obtaining the distance error model of the robot mechanical arm, the robot can calculate the parameter error of the real-time positioning of the robot terminal according to the functional relationship and the distance error model, so as to optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error, so as to calibrate the robot based on the obtained optimized kinematic parameters, thereby improving the efficiency and accuracy of robot calibration. Since the present application establishes the screw kinematic model of the robot based on the screw theory without additional measuring instruments, it can meet the requirements of the robot connecting rod for the completeness of the posture error and improve the accuracy of the error model. Since the present application adopts the distance error model of the mechanical arm to calculate the parameter error of the real-time positioning of the robot terminal, it does not rely on the coordinate system of the measurement system, reduces the influence of the coordinate system conversion error, effectively improves the calibration accuracy of the robot, and can meet the working requirements of the surgical site environment.

[0143] It should be understood that although Figure 1-Figure 5 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, although Figure 1-Figure 5At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0144] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0145] Please note that the above embodiments are for illustrative purposes only and are not intended to limit the present application. Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other.

[0146] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A robot parameter optimization method, characterized in that: include: Obtaining a screw kinematics model of the robot, and obtaining a functional relationship between a positioning error of the robot arm and a parameter error of the robot according to the screw kinematics model; Obtaining a distance error model of the robot manipulator, and calculating a parameter error of real-time positioning of the robot end according to the functional relationship and the distance error model; The robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot are optimized according to the parameter error of the real-time positioning of the robot end, including: Obtaining robot kinematic parameters corresponding to the real-time positioning instruction; Calculating a distance error vector according to the robot kinematic parameters; Calculating a distance error Jacobian matrix, and calculating a real-time distance error according to the distance error vector, the distance error Jacobian matrix and the distance error model; Determine whether the real-time distance error is greater than or equal to a preset error threshold; If so, a first preset algorithm is used to calculate the kinematic parameter error of the robot, and the corresponding kinematic parameters are updated according to the kinematic parameter error, so as to calculate the real-time distance error according to the updated kinematic parameters.

2. The method according to claim 1, characterized in that: The step of calculating the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model comprises: Obtaining the real-time positioning instruction, wherein the real-time positioning instruction is used to control the end of the robot to reach a preset measurement point; Obtaining the posture coordinates and a set of joint angles corresponding to the real-time positioning instruction when the robot end reaches any of the preset measurement points; The posture coordinates and a set of joint angles corresponding to each of the preset measurement points are input into the functional relationship and the distance error model to calculate the parameter error of the real-time positioning of the robot end.

3. The method according to claim 2, characterized in that The step of optimizing the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error comprises: If the real-time distance error does not satisfy or exceed a preset error threshold, the kinematic parameters are output.

4. A robot parameter calibration method, characterized in that: include: Obtaining a real-time positioning instruction, wherein the real-time positioning instruction is used to control a positioning terminal at the end of the robot to reach a preset measurement point; Acquire kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point; According to the kinematic parameters and the posture coordinates, the kinematic parameters are optimized using the robot parameter optimization method described in any one of claims 1 to 3, and the optimized kinematic parameters are obtained; The robot is calibrated according to the optimized kinematic parameters.

5. The method according to claim 4, characterized in that The step of calibrating the robot according to the optimized kinematic parameters comprises: Analyzing the kinematic parameters and obtaining the joint angles; Establishing a preset mathematical model according to the joint angle; Calculating the error transfer matrix of the joint angle, and calculating the posture error according to the error transfer matrix and the preset mathematical model; Determining whether the posture error is greater than or equal to a preset accuracy threshold; If yes, a second preset algorithm is used to calculate the joint angle error of the robot, and the corresponding joint angle is updated according to the joint angle error, so as to calculate the posture error according to the updated joint angle; Otherwise, the robot is calibrated according to the joint angles.

6. A robot parameter optimization device, characterized in that: include: A parameter error function acquisition module, used to acquire a screw kinematic model of the robot, and acquire a functional relationship between a positioning error of the robot manipulator and a parameter error of the robot according to the screw kinematic model; A parameter error calculation module is used to obtain a distance error model of the robot manipulator, and calculate the parameter error of the real-time positioning of the robot end according to the functional relationship and the distance error model; A parameter optimization module, used to optimize the robot kinematic parameters corresponding to the real-time positioning instruction obtained by the robot according to the parameter error of the real-time positioning of the robot end, and obtain the optimized kinematic parameters; wherein the parameter optimization module is specifically used to obtain the robot kinematic parameters corresponding to the real-time positioning instruction; Calculating a distance error vector according to the robot kinematic parameters; Calculating a distance error Jacobian matrix, and calculating a real-time distance error according to the distance error vector, the distance error Jacobian matrix and the distance error model; Determine whether the real-time distance error is greater than or equal to a preset error threshold; If so, a first preset algorithm is used to calculate the kinematic parameter error of the robot, and the corresponding kinematic parameters are updated according to the kinematic parameter error, so as to calculate the real-time distance error according to the updated kinematic parameters.

7. A robot parameter calibration device, characterized in that: include: A positioning instruction acquisition module is used to acquire real-time positioning instructions, wherein the instructions are used to control the positioning terminal at the end of the robot to reach a preset measurement point; A calibration data acquisition module, used to obtain kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point; The robot parameter optimization device according to claim 6, used to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and obtain the optimized kinematic parameters; A calibration module is used to calibrate the robot according to the optimized kinematic parameters.

8. A robot parameter calibration system, characterized in that: include: A calibration fixture, on which a plurality of preset measuring points are arranged; An end device is arranged at the end of the robot, and a positioning terminal is arranged at one end of the end device away from the end of the robot; The device as described in claim 6 or 7 is used to obtain the kinematic parameters and posture coordinates corresponding to the real-time positioning instruction when the positioning terminal reaches a preset measurement point, and to optimize the kinematic parameters according to the kinematic parameters and the posture coordinates, and to obtain the optimized kinematic parameters.

9. A robot comprising a robot body, a memory, a processor, and a computer program stored in the memory and executable by the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 5 are implemented.

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