Robot joint evaluation method and system, electronic equipment and storage medium

Abstract

The invention discloses a robot joint evaluation method and system, electronic equipment and a storage medium. The robot joint comprises a driving module, a fixed part and a sliding part. The driving module is used for driving the sliding part to move on the fixed part; acquiring the position information of the sliding part in the motion state and the corresponding friction force between the sliding part and the fixed part; fitting the friction force and the position information to obtain a friction force correction model; and evaluating the robot joint based on the parameters of the friction force correction model. According to the evaluation method of the robot joint, the friction force and the position information are fitted to obtain the friction force correction model, the robot joint is evaluated according to parameters of the friction force correction model, a scheme for evaluating whether joint installation is qualified or not is provided from the angle of robot control, and relation fitting of the friction force and the position of the robot joint is provided; the method can be used for correcting a classical friction force model, so that the robot control design requirement is met.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a robot joint evaluation method, system, electronic equipment and storage medium. Background Art

[0002] In recent years, the application of robots has achieved rapid development in various industries and played an increasingly important role. In high-end manufacturing and human-machine collaboration, human-machine interaction and other scenarios, higher requirements are also placed on the performance of robots. From the robot's configuration, mechanical design, processing, installation, to motor selection, parameter identification, and control strategy, each item is key to affecting the overall performance of the robot.

[0003] The design, processing and installation parallelism evaluation of robot joints are generally tested by various types of tooling and external precision measurement tools, such as laser measuring instruments. This method can theoretically guarantee the requirements of robot joints in subsequent robot control design. The more important parameter is the friction of the joints. The friction model can theoretically use the Coulomb+viscous model or the more accurate Lu-Gre model. However, in actual situations, due to various reasons, it is often impossible to ensure that the installation of robot joints meets the requirements of the friction theory model, so that the robot control design, especially the robot drag control, cannot achieve the expected effect. From the perspective of robot control design, it is a very urgent task to evaluate the installation of joints and provide corrections to the friction model. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defect in the prior art that the friction theory model is used to evaluate the robot joints, resulting in the robot control failing to achieve the expected results, and to provide a robot joint evaluation method, system, electronic device and storage medium.

[0005] The present invention solves the above technical problems through the following technical solutions:

[0006] The present invention provides an evaluation method for a robot joint, wherein the robot joint comprises a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; the evaluation method comprises:

[0007] Acquire position information of the sliding part in a moving state and the corresponding friction force between the sliding part and the fixed part;

[0008] Fitting the friction force and the position information to obtain a friction force correction model;

[0009] The robot joint is evaluated based on parameters of the friction correction model.

[0010] Preferably, the step of obtaining the position information of the sliding part in the moving state and the corresponding friction force between the sliding part and the fixed part comprises:

[0011] Acquire the position information of the sliding part in the motion state and the corresponding output torque of the driving module;

[0012] The friction force is determined based on the output torque.

[0013] Preferably, the robot joints include linear joints;

[0014] The step of fitting the friction force and the position information to obtain a friction force correction model comprises:

[0015] Construct a friction correction model based on exponential function;

[0016] The friction force and the position information are fitted using a least squares method to obtain optimal parameters of the friction force correction model.

[0017] Preferably, the friction correction model includes a friction component related to the position information and a friction component unrelated to the position information; the step of constructing the friction correction model based on the exponential function includes:

[0018] The friction force component associated with the position information is constructed based on an exponential function.

[0019] Preferably, the evaluation method further comprises:

[0020] Determining the friction force component that is independent of the position information based on the friction force at the starting end and / or the returning end of the movement of the sliding part; and / or,

[0021] The friction force and the position information are fitted using a least square method to obtain optimal parameters of the linearized friction force component associated with the position information.

[0022] Preferably, the parameters of the friction correction model include a parallelism parameter; the parallelism parameter is used to characterize the degree of parallelism between the fixed portion and the sliding portion;

[0023] The step of evaluating the robot joint based on the parameters of the friction correction model comprises:

[0024] Determining whether the parallelism parameter is less than a preset parallelism threshold;

[0025] If so, the robot joint is controlled based on a theoretical model of the friction force of the robot joint.

[0026] Preferably, after the step of determining whether the parallelism parameter is less than a preset parallelism threshold, the step of evaluating the robot joint based on the parameters of the friction correction model further includes:

[0027] If not, determining whether the robot joint is adjustable;

[0028] If so, adjusting the robot joint based on the parallelism parameter until the parallelism parameter is less than the preset parallelism threshold;

[0029] If not, the robot joint is controlled based on the friction force correction model of the robot joint.

[0030] The present invention also provides an evaluation system for a robot joint, wherein the robot joint comprises a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; the evaluation system comprises:

[0031] A data acquisition module, used to acquire position information of the sliding part in a moving state and the corresponding friction force between the sliding part and the fixed part;

[0032] A data fitting module, used for fitting the friction force and the position information to obtain a friction force correction model;

[0033] A joint evaluation module is used to evaluate the robot joint based on the parameters of the friction correction model.

[0034] Preferably, the data acquisition module is specifically used to acquire the position information of the sliding part in the motion state and the corresponding output torque of the driving module;

[0035] The data acquisition module is specifically configured to determine the friction force according to the output torque.

[0036] Preferably, the robot joints include linear joints;

[0037] The data fitting module is specifically used to construct a friction correction model based on an exponential function;

[0038] The data fitting module is specifically used to fit the friction force and the position information using the least squares method to obtain the optimal parameters of the friction force correction model.

[0039] Preferably, the friction correction model includes a friction component related to the position information and a friction component unrelated to the position information;

[0040] The data fitting module is specifically used to construct the friction force component related to the position information based on an exponential function.

[0041] Preferably, the evaluation system further comprises:

[0042] Determining the friction force component that is independent of the position information based on the friction force at the starting end and / or the returning end of the movement of the sliding part; and / or,

[0043] The friction force and the position information are fitted using a least square method to obtain optimal parameters of the linearized friction force component associated with the position information.

[0044] Preferably, the parameters of the friction correction model include a parallelism parameter; the parallelism parameter is used to characterize the degree of parallelism between the fixed portion and the sliding portion;

[0045] The joint evaluation module is specifically used to determine whether the parallelism parameter is less than a preset parallelism threshold;

[0046] If so, the joint evaluation module is specifically used to control the robot joint based on the friction theory model of the robot joint.

[0047] If not, the joint evaluation module is specifically used to determine whether the robot joint is adjustable;

[0048] If so, the joint evaluation module is specifically used to adjust the robot joint based on the parallelism parameter until the parallelism parameter is less than the preset parallelism threshold;

[0049] If not, the joint evaluation module is specifically configured to control the robot joint based on the friction correction model of the robot joint.

[0050] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the robot joint evaluation method as described above when executing the computer program.

[0051] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the robot joint evaluation method as described above.

[0052] The positive and progressive effects of the present invention are:

[0053] The robot joint evaluation method provided by the present invention obtains a friction correction model by fitting friction and position information, and evaluates the robot joints according to the parameters of the friction correction model; that is, from the perspective of robot control, a scheme for evaluating whether the joint installation is qualified is proposed, and a fitting of the relationship between the friction and position of the robot joint is proposed, which can be used to correct the classic friction model, thereby meeting the robot control design requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0055] Figure 1 This is the first flow chart of the robot joint evaluation method in Example 1 of the present invention.

[0056] Figure 2 This is a second flow chart of the robot joint evaluation method in Example 1 of the present invention.

[0057] Figure 3 This is the third flow chart of the robot joint evaluation method in Example 1 of the present invention.

[0058] Figure 4 This is the fourth flow chart of the robot joint evaluation method in Example 1 of the present invention.

[0059] Figure 5 This is a schematic diagram of the structure of a robot joint in Example 1 of the present invention.

[0060] Figure 6 It is a schematic diagram of the structure of the electronic device in Embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0061] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0062] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the text does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0063] As shown in this document, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural, unless the context clearly indicates an exception. Generally speaking, the terms "include" and "comprise" only indicate that the steps and elements that have been clearly identified are included, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0064] The definitions of first and second in this document and the descriptions of first, second, etc. that appear in this document are only used for illustration and distinction of the objects of description, and have no order, nor do they represent a special limitation on the number of devices in this document, and cannot constitute any limitation on this document. For example, a first element may be referred to as a second element without departing from the scope of this disclosure, and similarly, a second element may be referred to as a first element.

[0065] Flowcharts are used herein to illustrate the operations performed by the systems of the embodiments of this invention. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0066] Example 1

[0067] Please refer to Figure 1 , which is a first flow chart of the evaluation method of the robot joint in this embodiment. Specifically, the robot joint includes a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; Figure 1 As shown, the evaluation method includes:

[0068] S101, obtaining position information of a sliding part in a moving state and a corresponding friction force between the sliding part and a fixed part;

[0069] S102, fitting the friction force and position information to obtain a friction force correction model;

[0070] S103. Evaluate robot joints based on parameters of the friction correction model.

[0071] In an optional implementation, step S101 includes:

[0072] S1011, obtaining position information of the sliding part in a moving state and the output torque of the corresponding driving module;

[0073] S1012. Determine friction force according to output torque.

[0074] Specifically, the friction force is determined according to the following formula:

[0075] f=k·τ fric

[0076] Among them, f is the friction force, k is a constant, which is generally related to the motor torque constant, reducer reduction ratio and screw lead, τ fric is the output torque of the drive module.

[0077] Please refer to Figure 2, which is a second flow chart of the robot joint evaluation method in this embodiment. In this embodiment, the robot joint includes a linear joint; Figure 2 As shown, step S102 includes:

[0078] S1021. Construct a friction correction model based on an exponential function. Specifically, the exponential function includes a single exponential function, a double exponential function, etc. For linear joints, a single exponential function has a better fitting effect, and the optimization problem is easy to solve. For scenarios that require a double exponential function to fit, fitting can be performed using a data fitting tool.

[0079] S1022. Fit the friction force and position information using the least squares method to obtain optimal parameters of the friction force correction model.

[0080] In an optional implementation, the friction correction model is constructed according to the following formula:

[0081] f s =f s,new +f offset ;

[0082]

[0083] Among them, f s is the friction force between the sliding part and the fixed part, f s,new is the friction force component related to the position information, f offset is the friction force component that is independent of position information, a s and b s Parameters of the correction model for friction.

[0084] In another optional implementation, after step S1021, step S1022 includes:

[0085] S1023, determining a friction force component that is independent of position information according to the friction forces at the movement start end and the return end of the sliding part;

[0086] S1024. Fit the friction force and position information using the least squares method to obtain optimal parameters of the linearized friction force component associated with the position information.

[0087] Please refer to Figure 3, which is the third flow chart of the evaluation method for robot joints in this embodiment. In this embodiment, the parameters of the friction correction model include parallelism parameters; the parallelism parameters are used to characterize the degree of parallelism of the fixed part and the sliding part configuration; specifically, the joints of the robot are generally divided into two types: rotational joints and linear joints. Taking linear joints as an example, linear joints often use screw rods, and the parallelism of the screw rods is directly related to the friction of the linear joints, thereby affecting the performance of the entire robot, especially the design of the robot's drag control. The parallelism parameters can be used to determine whether the screw rod installation is qualified, and then determine which friction model to use to control the robot joints. Figure 3 As shown, step S103 includes:

[0088] S1031, determining whether the parallelism parameter is less than a preset parallelism threshold;

[0089] If yes, execute step S1032; if no, execute step S1033.

[0090] S1032. Control the robot joints based on a friction theory model of the robot joints.

[0091] S1033, determining whether the robot joints are adjustable;

[0092] If yes, execute step S1034; if no, execute step S1035.

[0093] S1034, adjusting the robot joints based on the parallelism parameter until the parallelism parameter is less than a preset parallelism threshold;

[0094] S1035. Control the robot joints based on the friction correction model of the robot joints.

[0095] like Figure 4 As shown, the evaluation method of the robot joint of this embodiment is further explained below by taking examples.

[0096] 1. Build a platform

[0097] Figure 5For a certain robot linear joint, place it horizontally. 101 is a motor module, which generally includes a motor, a reducer, an encoder, a brake, etc.; the motor module is driven by a driver, and the driver needs to ensure that the motor module can run at a constant speed; the driver power supply is generally a DC power supply; 102 is a transmission pulley, one end of the transmission pulley is connected to the motor output end, and the other end is connected to the screw 111. The rotation of the motor module drives the pulley to move, so that the screw rotates; at this time, the screw nut 112 can move from the proximal end 121 to the distal end 122, or move in the opposite direction; wherein the screw nut 112 and the slider 113 are connected together through parts, as the output end of the linear joint, the load can be installed. Since the slide rail 114 limits the movement direction of the slider, when the screw 111 is not parallel to the slide rail 114, the pressure between the slider and the slide rail will increase, thereby increasing the friction. Connect the installed linear joint to the driver and power supply, and connect the driver to the industrial computer, so that the linear joint movement can be controlled and data can be collected. Determine the zero position of the slide and let the slide be in the zero position. For example, the near end 121 can be defined as zero position x0, and the far end 122 can be defined as x final .

[0098] 2. Collect data

[0099] Turn on the platform, issue a motion command, move the linear joint from the proximal end to the distal end at a speed v, and start recording the motor output torque data τ in real time fric And the position x of the slide at this time; the sampling period can be selected according to the actual situation. Then, the friction force of the linear joint at this time is f = k·τ fric , where k is a constant, which is generally related to the motor torque constant, the speed reducer reduction ratio, and the lead of the screw. A torque sensor can also be directly installed at the output end of the motor module to obtain the friction force.

[0100] 3. Data processing and fitting

[0101] (1) Since the collected data can be processed offline, a delay-free filter can be used to filter out the burrs in the data. In general, the position data x is obtained by the encoder, which has fewer burrs and does not need to be filtered; the torque data of the motor has more burrs and needs to be filtered as τ fric,filted , then the friction force after filtering is f filted = k·τ fric,filted .

[0102] (2) In traditional friction identification, the relationship between position and friction is not considered; for example, in the Coulomb+viscous model or the more accurate Lu-Gre model, there is only a relationship between friction and speed. However, when the linear joints are not installed in parallel, the friction changes significantly with the change of position. At this time, the relationship between position and friction must be given priority. Use an exponential function to fit the relationship between friction and position. The optimized single exponential function is simpler to identify, and the double exponential function is more accurate. Optimized single exponential function Fitting friction: f offset The friction force is independent of the position. Usually, the minimum absolute value of the friction force after filtering can be taken as f offs , usually f offset =f filted (x=x final ) or f offset =f filted (x=x0), we need to The relationship between x and the least squares method can be used to obtain the optimal parameter a s and b s However, the solution of the nonlinear least squares problem is relatively complicated, so it is linearized. Taking the natural logarithm ln on both sides, we get set up Then there is So we can first find the data set The least squares fitting parameters of Thus we get The friction model is f s =f s,new +f offset . You can also use the double exponential function Friction force fitting is usually converted into an optimization problem for solution, which is a relatively complicated process. It can also be fitted using data fitting tools of mature software.

[0103] 4. Linear joint installation evaluation and friction correction

[0104] (1) Compared with the traditional friction model, this embodiment takes into account the relationship between friction and position, and can evaluate the installation of the linear joint through the specific model parameters of friction. s The absolute value of |b s | and b in the double exponential model d ,d d The maximum value of the absolute value of max(|b d |,|d d |) can be used to evaluate the installation quality of linear joints, that is, Figure 1 203λ=max(|bd |,|d d |) or λ=|b s |. A larger λ indicates a more non-parallel installation.

[0105] (2) At the same time, a suitable λ can be selected in 203 max , if λ<λ max This indicates that the linear joint is installed properly, and the classical friction model can be used in the subsequent robot control 207 design; otherwise, the installation is considered unqualified, but the joint can be adjusted, and the installation of the joint can be improved by adjusting the joint 205, and repeating steps 201, 202, and 203 until the qualified requirements are met;

[0106] (3) When the installation is unqualified and the joint adjustment is not allowed, this embodiment proposes to use the above exponential model as a compensation for the classical friction model, correct the classical friction model, complete 206, and use the corrected friction model in the robot control 207 design. Among them, the corrected friction model 206 can be obtained by the following scheme, for example: the classical friction model f trad (v) = f Coulomb +f viscous (v), the friction model after adding correction is f mod (x,v)=f trad (v)+f s,new (x)·sign(v), where sign(v) represents the sign of velocity. The revised model incorporates the relationship between friction and position, which can more clearly show the friction of robot joints in some special cases.

[0107] When the robot linear joints, rotary joints or other parts that require the use of classical friction models (Coulomb+viscous model, Lu-Gre model, etc.) may have friction that is position-dependent due to various factors. In this special case, the friction model can be identified by first identifying the friction model under the condition of constant speed. and f offset , and the classic friction model is modified according to the following formula: mod (x,v)=f trad (v)+(f(x)-f offset )·sign(v).

[0108] The robot joint evaluation method provided in this embodiment constructs a friction correction model based on an exponential function, uses the least squares method to fit the friction and position information to obtain the optimal parameters of the friction correction model, and determines whether to use the friction theoretical model or the friction correction model to control the robot joints according to the parallelism parameters of the friction correction model. That is, from the perspective of robot control, a scheme is proposed to evaluate whether the joint installation is qualified, and a fitting of the relationship between the friction and position of the robot joint is proposed, which can be used to correct the classic friction model, thereby meeting the robot control design requirements.

[0109] Example 2

[0110] This embodiment provides an evaluation system for a robot joint, wherein the robot joint comprises a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; the evaluation system comprises:

[0111] A data acquisition module, used to acquire position information of the sliding part in a moving state and the corresponding friction force between the sliding part and the fixed part;

[0112] A data fitting module, used for fitting friction and position information to obtain a friction correction model;

[0113] Joint evaluation module for parameter evaluation of robot joints based on a friction correction model.

[0114] Preferably, the data acquisition module is specifically used to acquire the position information of the sliding part in the motion state and the output torque of the corresponding driving module;

[0115] The data acquisition module is specifically used to determine the friction force according to the output torque.

[0116] Preferably, the robot joints include linear joints;

[0117] The data fitting module is specifically used to construct a friction correction model based on an exponential function;

[0118] The data fitting module is specifically used to fit the friction force and position information using the least squares method to obtain the optimal parameters of the friction force correction model.

[0119] Preferably, the friction correction model is constructed according to the following formula:

[0120] f s =f s,new +f offset ;

[0121]

[0122] Among them, f s is the friction force between the sliding part and the fixed part, fs,new is the friction force component related to the position information, f offset is the friction force component that is independent of position information, a s and b s Parameters of the correction model for friction.

[0123] Preferably, the evaluation system further comprises:

[0124] Determine the friction force component that is independent of the position information based on the friction force at the starting end and / or the returning end of the movement of the sliding part;

[0125] The friction force and position information are fitted using the least squares method to obtain the optimal parameters of the linearized friction force component related to the position information.

[0126] Preferably, the parameters of the friction correction model include a parallelism parameter; the parallelism parameter is used to characterize the degree of parallelism of the fixed part and the sliding part;

[0127] The joint evaluation module is specifically used to determine whether the parallelism parameter is less than a preset parallelism threshold;

[0128] If so, the joint evaluation module is specifically used to control the robot joints based on the friction theory model of the robot joints.

[0129] If not, the joint evaluation module is specifically used to determine whether the robot joint is adjustable;

[0130] If so, the joint evaluation module is specifically used to adjust the robot joints based on the parallelism parameter until the parallelism parameter is less than a preset parallelism threshold;

[0131] If not, the joint evaluation module is specifically used to control the robot joints based on the friction correction model of the robot joints.

[0132] As for the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is only schematic, in which the modules described as separate components may or may not be physically separated, and the modules displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the disclosed solution. Ordinary technicians in this field can understand and implement it without paying creative work.

[0133] Example 3

[0134] Figure 6This is a schematic diagram of the structure of an electronic device provided in Example 3 of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the robot joint evaluation method of Example 1 when executing the program. Figure 6 The electronic device 30 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0135] like Figure 6 As shown, the electronic device 30 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including the memory 32 and the processor 31).

[0136] The bus 33 includes a data bus, an address bus, and a control bus.

[0137] The memory 32 may include a volatile memory, such as a random access memory (RAM) 321 and / or a cache memory 322 , and may further include a read-only memory (ROM) 323 .

[0138] The memory 32 may also include a program / utility 325 having a set (at least one) of program modules 324, such program modules 324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0139] The processor 31 executes various functional applications and data processing by running the computer programs stored in the memory 32, such as the evaluation method of the robot joint of the first embodiment of the present disclosure.

[0140] The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 35. Furthermore, the model-generated device 30 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 36. As shown, the network adapter 36 communicates with other modules of the model-generated device 30 via a bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the model-generated device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (RAID) systems, tape drives, and data backup storage systems.

[0141] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0142] Example 4

[0143] This embodiment provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the robot joint evaluation method of Embodiment 1 is implemented.

[0144] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0145] In a possible implementation manner, the present disclosure may also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the robot joint evaluation method of Example 1.

[0146] Among them, the program code for executing the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0147] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A method for evaluating a robot joint, wherein the robot joint comprises a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; characterized in that: The evaluation methods include: Acquire position information of the sliding part in a moving state and the corresponding friction force between the sliding part and the fixed part; Fitting the friction force and the position information to obtain a friction force correction model; The robot joint is evaluated based on parameters of the friction correction model.

2. The evaluation method according to claim 1, characterized in that: The step of obtaining the position information of the sliding part and the corresponding friction force between the sliding part and the fixed part in the motion state comprises: Acquire the position information of the sliding part in the motion state and the corresponding output torque of the driving module; The friction force is determined based on the output torque.

3. The evaluation method according to any one of claims 1 or 2, characterized in that: The robot joints include linear joints; The step of fitting the friction force and the position information to obtain a friction force correction model comprises: Construct a friction correction model based on exponential function; The friction force and the position information are fitted using a least squares method to obtain optimal parameters of the friction force correction model.

4. The evaluation method according to claim 3, characterized in that: The friction correction model includes a friction component related to the position information and a friction component unrelated to the position information; The steps of constructing a friction correction model based on an exponential function include: The friction force component associated with the position information is constructed based on an exponential function.

5. The evaluation method according to claim 4, characterized in that: The evaluation method also includes: Determining the friction force component that is independent of the position information based on the friction force at the starting end and / or the returning end of the movement of the sliding part; and / or, The friction force and the position information are fitted using a least square method to obtain optimal parameters of the linearized friction force component associated with the position information.

6. The evaluation method according to any one of claims 1 to 5, characterized in that: The parameters of the friction correction model include a parallelism parameter; the parallelism parameter is used to characterize the degree of parallelism between the fixed part and the sliding part; The step of evaluating the robot joint based on the parameters of the friction correction model comprises: Determining whether the parallelism parameter is less than a preset parallelism threshold; If so, the robot joint is controlled based on a theoretical model of the friction force of the robot joint.

7. The evaluation method according to claim 6, characterized in that: After the step of determining whether the parallelism parameter is less than a preset parallelism threshold, the step of evaluating the robot joint based on the parameters of the friction correction model further includes: If not, determining whether the robot joint is adjustable; If so, adjusting the robot joint based on the parallelism parameter until the parallelism parameter is less than the preset parallelism threshold; If not, the robot joint is controlled based on the friction force correction model of the robot joint.

8. A robot joint evaluation system, the robot joint comprising a driving module, a fixed part and a sliding part; the driving module is used to drive the sliding part to move on the fixed part; characterized in that, The evaluation system comprises: A data acquisition module, used to acquire position information of the sliding part in a moving state and the corresponding friction force between the sliding part and the fixed part; A data fitting module, used for fitting the friction force and the position information to obtain a friction force correction model; A joint evaluation module is used to evaluate the robot joint based on the parameters of the friction correction model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the robot joint evaluation method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the robot joint evaluation method according to any one of claims 1 to 7 is implemented.

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