A robot evaluation method and device, electronic equipment and storage medium

Abstract

This application discloses a robot evaluation method, apparatus, electronic device, and storage medium. In response to a dragging operation on the end effector of a target robot, the method acquires the uniform motion speed and at least one force data of the target robot under uniform dragging. Based on the uniform motion speed and force data, the dragging damping parameter of the target robot is determined. Based on the force data, the dragging smoothness parameter and dragging consistency parameter of the target robot are determined respectively. Based on the dragging damping parameter, dragging smoothness parameter, and dragging consistency parameter, the compliance of the target robot is evaluated. This method provides a relatively objective, comprehensive, and accurate evaluation of the overall compliance of the target robot when dragged, proposing a practical verification and evaluation method to ensure that the robot's operational compliance is checked before use, thereby ensuring stable robot operation and improving robot safety.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a robot evaluation method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the continuous development of automation technology and the industrial upgrading of intelligent manufacturing-related industries, more and more manufacturers are working to improve their productivity to meet the ever-increasing production demands. Among these efforts, robotics, as a technology that can effectively reduce operating costs and improve work efficiency, is gaining popularity. Robots with multiple degrees of freedom, in particular, can effectively enhance productivity. However, multiple degrees of freedom mean greater structural complexity, necessitating the evaluation of these robots to ensure safe production.

[0003] Currently, for robot safety assessments, technicians evaluate the robot's working status by testing its temperature, vibration signals, and pressure levels. However, this method neglects pre-operation safety checks. If a serious malfunction occurs during operation, it can cause losses to the user and cannot guarantee the safety of the robot during direct operation. Summary of the Invention

[0004] This application provides a robot evaluation method, apparatus, robot, and storage medium to improve robot safety.

[0005] According to one aspect of this application, a robot evaluation method is provided, comprising:

[0006] In response to the dragging operation of the end effector of the target robot, acquire the uniform motion speed of the target robot under uniform dragging and at least one force data.

[0007] Based on the uniform motion speed and various force data, determine the drag damping parameters of the target robot;

[0008] Based on the force data, the drag smoothness parameters and drag consistency parameters of the target robot are determined respectively;

[0009] The compliance of the target robot is evaluated based on drag damping parameters, drag smoothness parameters, and drag consistency parameters.

[0010] According to another aspect of this application, a robot evaluation apparatus is provided, comprising:

[0011] The force data acquisition module is used to acquire the uniform motion speed of the target robot and at least one force data in response to the dragging operation of the end of the target robot.

[0012] The drag damping determination module is used to determine the drag damping parameters of the target robot based on the uniform motion speed and various force data.

[0013] The drag parameter determination module is used to determine the drag smoothness parameters and drag consistency parameters of the target robot based on various force data.

[0014] The machine compliance evaluation module is used to evaluate the compliance of the target robot based on drag damping parameters, drag smoothness parameters, and drag consistency parameters.

[0015] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the robot evaluation method described in any embodiment of this application.

[0019] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the robot evaluation method described in any embodiment of this application.

[0020] The technical solution of this application embodiment obtains the force data and uniform motion speed of the target robot's end effector during the dragging process, and then calculates various different index parameters of the target robot for evaluating its compliance, thereby evaluating its compliance. By determining the drag damping parameters, drag smoothness parameters, and drag consistency parameters of the target robot, a relatively objective, comprehensive, and accurate evaluation of the overall compliance of the robot when dragged is made. This proposes a practical verification and evaluation method to ensure that the robot's operational compliance is checked before use, thereby ensuring the robot's stable operation and improving its safety.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a robot evaluation method provided according to Embodiment 1 of this application;

[0024] Figure 2 This is a flowchart of a robot evaluation method according to Embodiment 2 of this application;

[0025] Figure 3A This is a schematic diagram of a robot used for robot compliance evaluation according to Embodiment 3 of this application;

[0026] Figure 3B This is a structural diagram of a robot compliance evaluation device applicable to Embodiment 3 of this application;

[0027] Figure 3C This is a flowchart of robot compliance evaluation used in Embodiment 3 of this application;

[0028] Figure 4 This is a schematic diagram of the structure of a robot evaluation device according to Embodiment 4 of this application;

[0029] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the robot evaluation method of the embodiments of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This application provides a flowchart of a robot evaluation method according to Embodiment 1. This embodiment is applicable to various situations where the method can be executed by a robot evaluation device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] S110, in response to the dragging operation of the end of the target robot, acquire the uniform motion speed of the target robot under uniform dragging and at least one force data.

[0035] The target robot can be a robot to be evaluated that is being dragged. The target robot can be a multi-degree-of-freedom serial or parallel robot. The overall compliance of the target robot is judged and evaluated by dragging its end effector (including but not limited to end joints, end links, or end grippers). The dragging operation can be performed manually or by another robot, by pulling the end effector of the target robot. Preferably, another robot is used for the dragging operation to ensure that the robot maintains a uniform speed during the dragging process. Currently, the dragging process is not unidirectional; preferably, it can be dragged back and forth in both directions to increase the sample size of the dragging process. Force data refers to the traction force received by the end effector of the target robot. Of course, the uniform speed can be measured by the target robot's own speed detection device; the force data can be obtained by installing a sensor (e.g., a six-dimensional force sensor) at the end effector of the target robot to measure the traction force generated by dragging the target robot. Therefore, multiple sets of force data can be obtained depending on the dragging direction and speed.

[0036] S120. Based on the uniform motion speed and various force data, determine the drag damping parameters of the target robot.

[0037] The drag damping parameter serves as a reference value representing the stiffness of the target robot's end effector under traction. It can be calculated based on the uniform motion velocity and the traction force received by the robot's end effector. Understandably, since the drag damping parameter reflects the target robot's drag stiffness characteristics, the traction force experienced during dragging must reflect the robot's stiffness when dragged. Given that there may be multiple uniform motion segments during dragging, there are multiple uniform motion velocities and force data points. The drag damping parameter is determined based on the ratio of these force data to the uniform motion velocity.

[0038] In one optional implementation, the dragging operation includes at least one forward dragging operation and at least one reverse dragging operation. The step of determining the dragging damping parameter of the target robot based on the uniform motion speed and various force data may include: determining the average force of the forward dragging operation and the reverse dragging operation based on various force data; and determining the dragging damping parameter based on the average force and the uniform motion speed.

[0039] Among them, forward push and reverse push are two dragging methods with opposite directions. The forward direction of dragging can be determined by relevant technicians based on the actual situation and / or human experience, and the opposite direction can be used as the reverse direction of dragging. Moreover, forward and reverse dragging operations can be performed more than once. Repeated dragging can collect more force data, which helps to more accurately determine the dragging compliance of the target robot.

[0040] The average force can be the average of the traction force experienced during multiple uniform motion segments of the towing process. It's understandable that, since force and velocity have direction, this calculation only considers the magnitude of the force and velocity—that is, the absolute values ​​of the force and the uniform motion velocity. First, the absolute values ​​of the traction force across multiple uniform motion segments are averaged. Then, the ratio of the average force to the uniform motion velocity is calculated and used as the towing damping parameter, as shown below:

[0041]

[0042] Where k is the drag damping parameter, ave() is the average value calculation, abs() is the absolute value calculation, V is the uniform motion velocity, and F is the force data. In the embodiments of this application, the velocities of different uniform motion segments in different directions are kept the same for ease of calculation.

[0043] S130. Based on the force data, determine the drag smoothness parameters and drag consistency parameters of the target robot respectively.

[0044] Among them, the drag smoothness parameter can be used to characterize the smoothness of the target robot under dragging force. The push-pull consistency parameter can be used to characterize the consistency of the robot's state when it is repeatedly dragged under moving forces in both directions.

[0045] It's understandable that, in different uniform motion segments where the end effector of the target robot receives towing, theoretically, assuming the robot's smoothness is excellent, using the same traction force can guarantee the same speed in each segment. However, in reality, the robot may experience varying degrees of smoothness when subjected to towing in different directions. To ensure a uniform motion speed, the magnitude of the traction force needs to be adjusted adaptively. In other words, the target robot receives different traction forces during towing processes with the same uniform motion speed but different directions. Therefore, the towing smoothness parameter and towing consistency parameter of the target robot can be determined based on the magnitude of the traction force in these different motion segments. The towing smoothness parameter can be calculated based on the magnitude of the traction force changes, while the towing consistency parameter can be calculated based on the magnitude of the traction force in each forward and reverse towing motion.

[0046] In one optional implementation, determining the drag smoothness parameter of the target robot based on the force data may include: calculating the standard deviation of the force data corresponding to the forward drag operation and the reverse drag operation; and using the standard deviation of the force as the drag smoothness parameter.

[0047] The force standard deviation can be the standard deviation of the traction force in different uniform motion segments of the target robot. By calculating the standard deviation of the traction force in each dragging process, the difference between the traction force and the average force in different dragging processes can be reflected. It should be noted that the standard deviation can well reflect the degree of deviation between different samples and the average value. In the application scenario of this application embodiment, the force standard deviation can reflect the degree of deviation between the traction force experienced in each uniform motion segment and the average traction force. Therefore, it can be understood that the force standard deviation also reflects the smoothness of the repeated dragging process of the target robot's end effector, and can be used as a parameter for dragging smoothness. The larger the force standard deviation, the worse the smoothness of the target robot during dragging; conversely, the smaller the force standard deviation, the better the smoothness of the target robot during dragging.

[0048] For example, the following formula can be used for calculation:

[0049] p = std(abs(F))

[0050] Where p is the drag smoothness parameter, std() is the standard value calculation, abs() is the absolute value calculation, and F is the force data.

[0051] In one optional implementation, determining the drag consistency parameter of the target robot based on the force data may include: determining the average value of the forward force and the average value of the reverse force based on the forward force data corresponding to the forward drag operation and the reverse force data corresponding to the reverse drag operation; and determining the drag consistency parameter based on the difference between the average value of the forward force and the average value of the reverse force.

[0052] The force data generated by forward dragging is called forward force data, and the force data generated by reverse dragging is called reverse force data. The average forward force is the average of all forward force data; the average reverse force is the average of all reverse force data. The difference between the average forces in the two directions is used to determine the consistency of the forward and reverse dragging during repeated dragging of the target robot's end effector.

[0053] For example, the following formula can be used for calculation:

[0054] r = abs(ave(abs(F) + ))-ave(abs(F-))

[0055] Where r is the drag-and-drop consistency parameter, F + F- represents the positive force data, and F- represents the negative force data.

[0056] S140. Evaluate the compliance of the target robot based on the drag damping parameter, drag smoothness parameter, and drag consistency parameter.

[0057] The compliance of the target robot is comprehensively evaluated based on the drag damping parameters, push smoothness parameters, and drag consistency parameters determined in the preceding steps. For example, weight values ​​can be pre-set for the above three parameters, and the compliance score can be obtained by calculating the weighted sum of the above three parameters, which can then be used as the compliance evaluation result.

[0058] In one optional embodiment, evaluating the compliance of the target robot based on drag damping parameters, drag smoothness parameters, and drag consistency parameters may include: determining drag damping deviation rate, drag smoothness deviation rate, and drag consistency deviation rate respectively based on preset expected values ​​for drag damping, drag smoothness, and drag consistency, as well as the drag damping parameters, drag smoothness parameters, and drag consistency parameters; and determining evaluation parameters for robot compliance based on the drag damping deviation rate, drag smoothness deviation rate, drag consistency deviation rate, and preset weighting coefficients.

[0059] Among these, the expected drag damping value can be an ideal value set for the drag damping parameter; similarly, the expected drag smoothness value can be an ideal value set for the drag smoothness parameter; and the expected drag consistency value can be an ideal value set for the drag consistency parameter. Under these ideal values, the target robot possesses theoretically the best compliance. In practice, compliance can be used to describe the smoothness of the robot during dragging, that is, whether it can smoothly complete the change in posture at the end of the dragging process.

[0060] The drag damping deviation rate can be the difference between the drag damping parameter and the expected drag damping value, expressed as a percentage of the expected drag damping value. Similarly, the drag smoothness deviation rate can be the difference between the drag smoothness parameter and the expected drag smoothness value, expressed as a percentage of the expected drag smoothness value. The drag consistency deviation rate can be the difference between the drag consistency parameter and the expected drag consistency value, expressed as a percentage of the expected drag consistency value. These three deviation rates reflect the difference between each indicator and its expected value. By setting different weight ratios, the evaluation parameters are calculated. The preset weight coefficients can be set by relevant technical personnel based on actual conditions or human experience. For example, the weight coefficient corresponding to the drag damping deviation rate can be adjusted to be larger; however, this application does not limit this.

[0061] For example, the evaluation parameters of compliance can be calculated according to the following formula:

[0062]

[0063] a1 + a2 + a3 = 1

[0064] Where res is the evaluation parameter for the compliance of the target robot. K is the expected value of drag damping, P is the expected value of drag smoothness, R is the expected value of drag consistency, a1 is the drag damping weight coefficient, a2 is the drag smoothness weight coefficient, and a3 is the drag consistency weight coefficient.

[0065] The technical solution of this application embodiment obtains the force data and uniform motion speed of the target robot's end effector during the dragging process, and then calculates various different index parameters of the target robot for evaluating its compliance, thereby evaluating its compliance. By determining the drag damping parameters, drag smoothness parameters, and drag consistency parameters of the target robot, a relatively objective, comprehensive, and accurate evaluation of the overall compliance of the robot when dragged is made. This proposes a practical verification and evaluation method to ensure that the robot's operational compliance is checked before use, thereby ensuring the robot's stable operation and improving its safety.

[0066] Example 2

[0067] Figure 2 This is a flowchart of a robot evaluation method provided in Embodiment 2 of this application. This embodiment is based on the foregoing embodiments, with additional optimization operations for the target robot. Figure 2 As shown, the method includes:

[0068] S210, in response to the dragging operation of the end of the target robot, acquire the uniform motion speed of the target robot under uniform dragging and at least one force data.

[0069] S220. Based on the uniform motion speed and various force data, determine the drag damping parameters of the target robot.

[0070] S230. Based on the force data, determine the drag smoothness parameters and drag consistency parameters of the target robot respectively.

[0071] S240. Evaluate the compliance of the target robot based on the drag damping parameter, drag smoothness parameter, and drag consistency parameter.

[0072] S250, in response to the dragging operation of the end of the target robot, obtain the dragging torque of the end of the target robot.

[0073] The dragging torque can be obtained through a six-dimensional force sensor installed at the end of the target robot. In other words, obtaining the dragging torque and force data of the target robot can be done simultaneously, without any specific order of execution.

[0074] S260. Optimize the target robot based on the drag torque and drag damping parameters.

[0075] Since drag torque and drag damping parameters can directly reflect the relationship between joint torque and various friction torques during the dragging process of the target robot, various friction torques can be adaptively adjusted by drag torque and drag damping parameters to optimize the dragging performance of the target robot.

[0076] It should be noted that, taking a serial robot as an example, when the end of the serial robot is dragged, the following drag-and-drop relationship exists:

[0077] τ 关节 =τ 重力 +k1·τ 静摩擦 +k2·τ 粘滞摩擦 +k3·τ 库伦摩擦

[0078] Where τ represents different torques, the above formula expresses that the joint torque is determined by the gravitational torque, static friction torque, viscous friction torque and Coulomb friction torque acting on the joint, k1 is the static friction compensation coefficient, k2 is the viscous friction compensation coefficient and k3 is the Coulomb friction compensation coefficient.

[0079] It should be noted that joint torque is used to compensate for the gravity, static friction, viscous friction and Coulomb friction inherent in the target robot itself. It is equivalent to using joint torque to counteract the various torques inherent in the robot.

[0080] In one optional implementation, optimizing the target robot based on the dragging torque and dragging damping parameters may include: increasing the static friction compensation coefficient of the target robot if the dragging torque is greater than a preset starting torque; increasing the viscous friction compensation coefficient and Coulomb friction compensation coefficient of the target robot if the dragging damping is greater than a preset damping threshold range; and decreasing the viscous friction compensation coefficient and Coulomb friction compensation coefficient if the dragging damping is less than a preset damping threshold range.

[0081] The starting torque can be defined as the maximum torque required for the end effector of the target robot to be dragged normally. If the obtained dragging torque is greater than the starting torque, it indicates that dragging is difficult, meaning that the static friction of the target robot is relatively large. This problem can be overcome by increasing the static friction compensation coefficient. Therefore, the static friction compensation coefficient can be increased.

[0082] The damping threshold range can be defined as the range of damping forces within which the target robot's end effector can be dragged normally. If the dragging damping exceeds the damping threshold range, it indicates that the robot's current viscous friction and Coulomb friction are relatively high, which can be addressed by increasing the viscous friction compensation coefficient and the Coulomb friction compensation coefficient.

[0083] Similarly, if the dragging damping is less than the damping threshold range, it means that the robot's current viscous friction and Coulomb friction are relatively small, which can be addressed by reducing the viscous friction compensation coefficient and the Coulomb friction compensation coefficient.

[0084] The technical solution of this application optimizes the target robot by adjusting the compensation coefficient for different friction forces based on dragging torque and dragging damping parameters. This effectively compensates for dragging irregularities caused by varying friction forces, thereby specifically improving the robot's performance and further ensuring its safety during operation.

[0085] Example 3

[0086] Figure 3AThis is a schematic diagram of robot dragging provided in Embodiment 3 of this application. This embodiment is a preferred embodiment provided based on the foregoing implementation methods. This embodiment takes the example of the target robot's end being dragged twice in each direction (a total of four uniform motion segments).

[0087] like Figure 3A As shown in the figure, this embodiment uses a towing robot to pull a target robot as an example. Robot a is the towing robot; robot b is the target robot, which is the robot being towed and whose compliance needs to be evaluated; c is the connection device between a and b, which may include a sensor for detecting the towing force.

[0088] like Figure 3B As shown, the technical solution of this application embodiment mainly includes the following 8 modules: drag-assisted motion module 301; force / motion measurement module 302; connection module 303; target robot 304; robot control unit 305; drag quantification evaluation module 306; drag optimization module 307; and auxiliary motion control unit 308.

[0089] Among them, the drag-assisted motion module 301 includes a mechanical device for traction of the test end of the target robot, which has multi-dimensional motion capability, the motion dimension covers the target robot, and the mechanical stiffness is much greater than that of the robot under test; for example, the target robot is a traditional 6-axis robot or a 2-dimensional planar motion robot, and the drag-assisted motion mechanism can preferably be a high-stiffness, high-load 6-axis robot whose motion space completely covers the target robot.

[0090] The force / motion measurement module 302 includes devices such as position measurement sensors and force measurement sensors that can sense the motion and force applied to the test end of the sensor under test. Examples include a six-dimensional force sensor and an absolute position encoder.

[0091] The connection module 303 includes a device for connecting the drag-assist motion module and the target robot test end. This device transmits the motion of the assist motion module to the target robot test end, causing the target robot test end to generate the desired motion while dragging the assist motion module. Generally, the connection module also serves to connect the fixed measurement module 302.

[0092] Target robot 304 includes the robotic device to be evaluated.

[0093] The robot control unit 305 includes a control, calculation, and storage unit for the target robot.

[0094] The drag-and-drop evaluation module 306 can be used as a sub-module for evaluating target input, receiving process data, analyzing process data, and outputting evaluation results. The main functions of this module are to receive the target input, receive the drag-and-drop process data, perform quantitative analysis on the process data, and finally output the quantitative analysis results.

[0095] The drag-and-drop optimization module 307 includes sub-modules for optimizing drag-and-drop target input, receiving drag-and-drop evaluation results, optimizing calculation and analysis, and inputting optimization results. The main function of this module is to receive the drag-and-drop optimization target input and the drag-and-drop evaluation results, perform optimization calculations based on the two, and finally output the optimized transformation relationship parameters.

[0096] The auxiliary motion control unit 308 includes a control, calculation, and storage unit for the auxiliary motion device.

[0097] according to Figure 3C As shown, the evaluation process for the compliance of the target robot is as follows:

[0098] In step 3001, preparations are made to begin evaluating and optimizing robot dragging.

[0099] In step 3002, the target robot is installed, and the mechanical and electrical connections between the dragging auxiliary motion device 301, the measuring device 302, and the target robot 304 are completed.

[0100] In step 3003, the robot test space is determined based on the actual movement range of each robot or the allowable drag range set by the robot, and the space information is input to the auxiliary motion control unit 308.

[0101] In step 3004, the auxiliary motion control unit 308 automatically generates a test trajectory based on the information input in 3003. The test trajectory can also be manually input by the operator.

[0102] In step 3005, the dragging function of the target robot is first activated. The auxiliary dragging motion control unit 308 controls the auxiliary dragging motion device 301. The auxiliary dragging motion device 301 drives the target robot 304 to move through the connecting device 303, simulating the working condition of a person dragging a robot.

[0103] In step 3006, the test signal from the sensing unit 302 of the target robot 304 during the dragging process in step 3005 is acquired in real time and transmitted to the evaluation unit 306. The transmission can be performed in real time or after the movement is completed.

[0104] In step 3007, based on the specified dragging boundary conditions, such as maximum dragging speed limits and dragging pose limits (joint limits), the auxiliary robot's motion trajectory includes the end of the trajectory that exceeds the target robot's maximum allowable dragging speed limit. The auxiliary robot controller monitors the target robot controller's dragging overspeed alarm output and dragging over-limit output to determine whether the target robot meets the dragging boundary condition requirements. The evaluation module 306 determines whether the target robot's movement 304 is within the dragging boundary conditions. If it exceeds the boundary conditions, it determines whether the robot has responded correctly. The dragging boundary conditions are determined by the operator; they can be manually input or read from the robot's configuration file. The response exceeding the robot's dragging boundaries is determined by the operator, and the impact status can be transmitted to the evaluation module 306 through specific communication methods, such as signal line connections or network signal transmission.

[0105] In step 3008, if the target robot 304 does not react correctly when the dragging boundary is exceeded, the test terminates, and the evaluation module 306 may notify the staff in some form; if the target robot 304 reacts correctly when the dragging boundary is exceeded, the next step continues.

[0106] In step 3009, the compliance of the target robot is evaluated according to the robot evaluation method provided in Embodiment 1 of this application, and the drag compliance index of the target robot 304 (such as the drag damping parameter, drag smoothness parameter and drag consistency parameter mentioned in Embodiment 1 above) is calculated.

[0107] In step 3010, if the evaluation result of evaluation unit 306 meets the set drag smoothness requirements, the evaluation ends. If it does not meet the requirements, proceed to the next step.

[0108] In step 3011, based on the results of evaluation unit 306, drag optimization module 307 automatically calculates drag-related parameters and transmits them to robot control module 305 to modify the robot drag-related parameters (as shown in the robot optimization operation in Embodiment 2 above). After modifying the robot drag-related parameters, steps 3005 to 3011 are repeated iteratively until the drag compliance meets the requirements in step 3010. Some robots may have serious hardware problems, causing the drag compliance to consistently fail to meet the requirements. In such cases, the operator can set a maximum number of iterations to terminate the drag compliance iteration.

[0109] Example 4

[0110] Figure 4 This is a schematic diagram of the structure of a robot evaluation device provided in Embodiment 3 of this application. Figure 4 As shown, the device 400 includes:

[0111] The force data acquisition module 410 is used to acquire the uniform motion speed of the target robot and at least one force data in response to the dragging operation of the end of the target robot.

[0112] The drag damping determination module 420 is used to determine the drag damping parameters of the target robot based on the uniform motion speed and various force data.

[0113] The drag parameter determination module 430 is used to determine the drag smoothness parameter and drag consistency parameter of the target robot based on the force data.

[0114] The machine compliance evaluation module 440 is used to evaluate the compliance of the target robot based on drag damping parameters, drag smoothness parameters, and drag consistency parameters.

[0115] The technical solution of this application embodiment obtains the force data and uniform motion speed of the target robot's end effector during the dragging process, and then calculates various different index parameters of the target robot for evaluating its compliance, thereby evaluating its compliance. By determining the drag damping parameters, drag smoothness parameters, and drag consistency parameters of the target robot, a relatively objective, comprehensive, and accurate evaluation of the overall compliance of the robot when dragged is made. This proposes a practical verification and evaluation method to ensure that the robot's operational compliance is checked before use, thereby ensuring the robot's stable operation and improving its safety.

[0116] In one alternative embodiment, the dragging operation includes at least one forward dragging operation and at least one reverse dragging operation, and the drag damping determination module 420 may include:

[0117] The average force determination unit is used to determine the average force for forward and reverse drag operations based on the force data.

[0118] The damping parameter determination unit is used to determine the drag damping parameters based on the average force and the uniform motion speed.

[0119] In one alternative implementation, the drag parameter determination module 430 may include:

[0120] The force standard deviation calculation unit is used to calculate the force standard deviation of each force data corresponding to the forward drag operation and the reverse drag operation; the force standard deviation is used as a drag smoothness parameter.

[0121] In one alternative implementation, the drag parameter determination module 430 may include:

[0122] The force average value determination unit is used to determine the average value of the forward force and the average value of the reverse force based on the forward force data corresponding to the forward drag operation and the reverse force data corresponding to the reverse drag operation, respectively.

[0123] The consistency parameter determination unit is used to determine the drag consistency parameter based on the difference between the average value of the positive force and the average value of the negative force.

[0124] In one alternative embodiment, the machine compliance evaluation module 440 may include:

[0125] The deviation rate determination module is used to determine the drag damping deviation rate, drag smoothness deviation rate, and drag consistency deviation rate respectively based on the preset drag damping expectation value, drag smoothness expectation value, drag consistency expectation value, drag damping parameter, drag smoothness parameter, and drag consistency parameter.

[0126] The evaluation parameter determination module is used to determine the evaluation parameters of robot compliance based on the drag damping deviation rate, drag smoothness deviation rate, drag consistency deviation rate, and preset weighting coefficients.

[0127] In one alternative embodiment, the robot evaluation device 400 may further include:

[0128] The drag torque acquisition module is used to acquire the drag torque of the target robot's end effector in response to the dragging operation of the end effector of the target robot.

[0129] The robot optimization module is used to optimize the target robot based on drag torque and drag damping parameters.

[0130] In one alternative implementation, the robot optimization module may include:

[0131] The static friction compensation unit is used to increase the static friction compensation coefficient of the target robot if the dragging torque is greater than the preset starting torque.

[0132] The viscous and Coulomb friction compensation module is used to increase the viscous friction compensation coefficient and the Coulomb friction compensation coefficient of the target robot if the dragging damping is greater than the preset damping threshold range; and to decrease the viscous friction compensation coefficient and the Coulomb friction compensation coefficient if the dragging damping is less than the preset damping threshold range.

[0133] The robot evaluation device provided in this application embodiment can execute the robot evaluation method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing each robot evaluation method.

[0134] Example 5

[0135] Figure 5A schematic diagram of an electronic device 10, which can be used to implement embodiments of this application, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0136] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0137] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0138] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as robot evaluation methods.

[0139] In some embodiments, the robot evaluation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the robot evaluation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the robot evaluation method by any other suitable means (e.g., by means of firmware).

[0140] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0142] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0144] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0145] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0146] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0147] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A robot evaluation method, characterized in that, include: In response to a dragging operation at the end of a target robot, the uniform motion speed of the target robot under uniform dragging and at least one force data are acquired; wherein the dragging operation includes at least one forward dragging operation and at least one reverse dragging operation. Based on the uniform motion speed and the force data, the drag damping parameters of the target robot are determined; Calculate the standard deviation of the force data corresponding to the forward drag operation and the reverse drag operation, and use the standard deviation of the force as a drag smoothness parameter; Based on the positive force data corresponding to the positive drag operation and the negative force data corresponding to the negative drag operation, the average positive force and the average negative force are determined respectively. The drag consistency parameter is determined based on the difference between the average value of the positive force and the average value of the negative force. The compliance of the target robot is evaluated based on the drag damping parameter, the drag smoothness parameter, and the drag consistency parameter.

2. The method according to claim 1, characterized in that, The step of determining the drag damping parameters of the target robot based on the uniform motion speed and the force data includes: Based on the force data, determine the average force of the forward drag operation and the reverse drag operation; The drag damping parameters are determined based on the average force and the uniform motion speed.

3. The method according to any one of claims 1-2, characterized in that, The evaluation of the compliance of the target robot based on the drag damping parameter, the drag smoothness parameter, and the drag consistency parameter includes: Based on the preset expected values ​​of drag damping, drag smoothness, and drag consistency, as well as the drag damping parameters, drag smoothness parameters, and drag consistency parameters, the drag damping deviation rate, drag smoothness deviation rate, and drag consistency deviation rate are determined respectively. The evaluation parameters for robot compliance are determined based on the drag damping deviation rate, the drag smoothness deviation rate, the drag consistency deviation rate, and a preset weighting coefficient.

4. The method according to any one of claims 1-2, characterized in that, The method further includes: In response to a dragging operation at the end of the target robot, the dragging torque of the end of the target robot is obtained; The target robot is optimized based on the drag torque and the drag damping parameters.

5. The method according to claim 4, characterized in that, The optimization of the target robot based on the dragging torque and the dragging damping parameters includes: If the dragging torque is greater than the preset starting torque, the static friction compensation coefficient of the target robot will be increased; If the dragging damping is greater than the preset damping threshold range, the viscous friction compensation coefficient and the Coulomb friction compensation coefficient of the target robot will be increased. If the dragging damping is less than the preset damping threshold range, the viscous friction compensation coefficient and the Coulomb friction compensation coefficient will be reduced.

6. A robot evaluation device, characterized in that, include: The force data acquisition module is used to acquire the uniform motion speed of the target robot and at least one force data in response to the dragging operation of the end of the target robot; wherein the dragging operation includes at least one forward dragging operation and at least one reverse dragging operation. The drag damping determination module is used to determine the drag damping parameters of the target robot based on the uniform motion speed and the force data. The drag parameter determination module is used to determine the drag smoothness parameter and drag consistency parameter of the target robot based on the force data. The machine compliance evaluation module is used to evaluate the compliance of the target robot based on the drag damping parameter, the drag smoothness parameter, and the drag consistency parameter. The drag parameter determination module includes: The force standard deviation calculation unit is used to calculate the force standard deviation of each force data corresponding to the forward drag operation and the reverse drag operation, and use the force standard deviation as the drag smoothness parameter; The drag parameter determination module includes: The average force determination unit is used to determine the average forward force and the average reverse force based on the average forward force data corresponding to the forward drag operation and the average reverse force data corresponding to the reverse drag operation, respectively. The consistency parameter determination unit is used to determine the drag consistency parameter based on the difference between the average value of the positive force and the average value of the negative force.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the robot evaluation method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the robot evaluation method according to any one of claims 1-5.

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