Parallel robot coupling gain adjusting method, device and equipment based on visual recognition and storage medium

Abstract

The invention provides a parallel robot coupling gain adjusting method, device and equipment based on visual recognition and a storage medium. Relates to the technical field of machine vision, robots and automation. The method comprises the following steps: acquiring the position of an object and the position of a working space, and calculating the distance from the object to the center of the working space according to the object position and the position of the working space; calculating an inertia coupling index of each driving shaft according to the self-load inertia and the inter-shaft coupling inertia of the driving shafts; setting a speed threshold value and an acceleration threshold value of each joint of the parallel robot, and when the speed of each joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determining a correction value according to the distance from an object to the center of a working space and an inertia coupling index of a driving shaft; and on the basis of the correction value, the fuzzy adjustment amount of the controller parameters of the parallel robot is determined. According to the method, the influence of the coupling action torque between the joints on the tracking precision of a control system during high-speed movement can be effectively reduced.

Description

Technical Field

[0001] The present application relates to the technical fields of machine vision, robotics, and automation, and particularly relates to a method, device, equipment, and storage medium for adjusting the coupling gain of a parallel robot based on visual recognition. Background Art

[0002] For modern new industrial robots, PID controllers are generally adopted. Such controllers have the advantages of simple structure, easy calculation, high reliability, etc. However, it is difficult for controllers with fixed gains to meet the requirements of high-speed and high-precision in the entire working space of industrial robots. As a new type of controller, fuzzy PID has the advantages of high robustness and strong reliability, and can autonomously perform self-tuning of PID parameters. However, for the disturbance generated by the joint force during the movement of high-speed parallel robots, the following accuracy level is relatively low, making it difficult to meet industrial requirements. At the same time, when the robot moves, due to the inability to accurately locate the position of the moving object, the coupling force between joints becomes disordered. Therefore, there is an urgent need for a fuzzy coupling control method suitable for visual industrial robots, which combines the pixel difference of the target object, the fuzzy algorithm, and the correction coefficient considering the coupling effect to improve the motion accuracy of industrial robots. Summary of the Invention

[0003] The present application provides a method, device, equipment, and storage medium for adjusting the coupling gain of a parallel robot based on visual recognition, which can effectively reduce the influence of the disturbance generated by the coupling force between joints during the high-speed movement of the parallel robot on the control system.

[0004] In a first aspect, the present application provides a method for adjusting the coupling gain of a parallel robot based on visual recognition, including: Obtain the position of the object and the position in the working space, and calculate the distance from the object to the center of the working space according to the position of the object and the position in the working space; Calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia; Set the speed threshold value and acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine a correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; Based on the correction value, determine the fuzzy adjustment amount of the controller parameters of the parallel robot.

[0005] In a possible design, calculate the distance from the object to the center of the working space according to the position of the object and the position in the working space h as: ; wherein, x p, y p , z p are the position coordinates of the object respectively, x o , y o , z o are the position coordinates of the workspace respectively.

[0006] In a possible design, according to the self-load inertia of the drive shaft and the inter-axis coupling inertia, the inertia coupling index of each drive shaft is calculated by the following formula: ; In the formula, ICI i represents the inertia coupling index of the drive shaft, represents the coupling strength coefficient, e represents the base of the natural logarithm, M g ( i , j ) represents a symmetric positive definite matrix, including the self-load inertia of the drive shaft and the inter-axis coupling inertia, i represents the controlled joint, j represents the other joints except the controlled joint, and n represents the number of drive joints of the parallel robot.

[0007] In a possible design, the joints of the parallel robot include screw drive joints. When the speed of the screw drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, according to the distance from the object to the center of the workspace and the inertia coupling index of the drive shaft, the first correction value is determined by the following formula: ; In the formula, represents the first correction value, and represent the speed threshold value and the acceleration threshold value of the corresponding joints of the parallel robot respectively, and represent the joint speed and acceleration of the parallel robot respectively, h represents the distance from the object to the center of the workspace, represents the first correction factor.

[0008] In a possible design, based on the first correction value, the fuzzy adjustment amount of the controller parameters of the screw drive joints of the parallel robot is determined by the following formula: ; ; ; In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the derivative parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the derivative parameter adjustment amount.

[0009] In a possible design, the joint of the parallel robot includes a branch chain drive joint. When the speed of the branch chain drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft, the second correction value is determined by the following formula: ; In the formula, represents the second correction value, and respectively represent the speed threshold value and the acceleration threshold value of the corresponding joint of the parallel robot, and respectively represent the joint speed and acceleration of the parallel robot, h represents the distance from the object to the center of the working space, represents the second correction factor.

[0010] In a possible design, based on the second correction value, the fuzzy adjustment amount of the controller parameters of the branch chain drive joint of the parallel robot is determined by the following formula: ; ; ; In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the derivative parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the derivative parameter adjustment amount.

[0011] Second, this application provides a coupling gain adjustment device for a parallel robot based on visual recognition. The device includes a controller, and the controller is configured to: A vision processing module, configured to obtain the position of an object and the position of a working space, and calculate the distance from the object to the center of the working space according to the position of the object and the position of the working space; A coupling index calculation module, configured to calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia; A correction value calculation module, configured to set the speed threshold value and acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine a correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; An adjustment amount calculation module, configured to determine a fuzzy adjustment amount of the controller parameters of the parallel robot based on the correction value.

[0012] In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor and a memory; the memory stores computer execution instructions; the at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the vision recognition-based parallel robot coupling gain adjustment method described in the first aspect and various possible designs of the first aspect above.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the vision recognition-based parallel robot coupling gain adjustment method described in the first aspect and various possible designs of the first aspect above is implemented.

[0014] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the vision recognition-based parallel robot coupling gain adjustment method described in the first aspect and various possible designs of the first aspect above is implemented.

[0015] The vision recognition-based parallel robot coupling gain adjustment method, device, equipment and storage medium provided by the present application have at least the following beneficial effects: The present application proposes a correction coefficient (correction value) based on the pixel difference of an object. By collecting, judging and calculating the speed and acceleration between robot joints, and the recognition of the pixel difference of the target object by a camera, the fuzzy adjustment of the controller parameters of the controlled joints is realized. The advantage of the present invention is that when performing fuzzy correction, it is not necessary to accurately identify the mathematical model of the controlled object. At the same time, considering the coupling effect between joints and the pixel difference of the target object, the calculation method is simple, the hardware resources occupied are less, and it is easy to implement. Description of the Drawings

[0016] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present application and, together with the specification, are used to explain the principles of the present application.

[0017] Figure 1 It is a diagram of an application scenario of a method for adjusting the coupling gain of a parallel robot based on visual recognition provided for an embodiment of the present application; Figure 2 It is a flowchart of a method for adjusting the coupling gain of a parallel robot based on visual recognition provided for an embodiment of the present application; Figure 3 It is a control flowchart of a method for adjusting the coupling gain of a parallel robot based on visual recognition provided for an embodiment of the present application; Figure 4 It is a structural diagram of a device for adjusting the coupling gain of a parallel robot based on visual recognition provided for an embodiment of the present application.

[0018] Through the above accompanying drawings, specific embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and written descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Specific Embodiments

[0019] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0020] In the technical solution of the present application, the collection, storage, use, processing, transmission, provision, and disclosure of information such as financial data or user data comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0021] It should be noted that in the embodiments of the present application, some industry-existing solutions such as certain software, components, models, etc. may be mentioned. They should be considered exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solution of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0022] The following uses specific embodiments to detail the technical solution of the present application and how the technical solution of the present application solves the above technical problems. These several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following will describe the embodiments of the present application with reference to the accompanying drawings.

[0023] An embodiment of the present application provides a method for adjusting the coupling gain of a parallel robot based on visual recognition. As Figure 1 shown, it is an application scenario diagram of a method for adjusting the coupling gain of a parallel robot based on visual recognition provided by an embodiment of the present application. As Figure 1 shown, the control method of a traditional parallel robot is implemented using a PID controller and a fuzzy controller. Its basic principle is to add a fuzzy supervision layer on the basis of PID control to dynamically correct the PID output. In the traditional control method, the fuzzy controller uses the error and its change rate as input variables. After fuzzy processing and fuzzy inference, the fuzzy controller generates an output for adjusting the fuzzy correction amounts of the proportional, integral, and differential parameters of the controller of each drive joint of the robot. Among them, the error and its change rate can be determined by the PID controller, and the generated fuzzy correction amount is directly fed back to the PID controller. The PID controller outputs control parameters to the controlled servo system, thereby controlling the parallel robot.

[0024] In the present application, on the basis of the traditional control method, a vision system and a correction coefficient are added, and the fuzzy correction amount of the controller parameters is adjusted by considering the coupling effect between joints. Generally speaking, in Figure 1 , j = 1, 2 represent the two lead screws of the parallel robot, and j = 3, 4 represent the two branch chains of the parallel robot, h represents the distance from the object to the working space, and respectively represent the joint speed and acceleration of the parallel robot, represents the initial value of the controller parameters, represents the controller parameters adjusted by the adjustment algorithm, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the differential parameter adjustment amount output by the fuzzy controller, ICI i represents the inertia coupling index of each drive axis in the joint space of the parallel robot. The vision system determines the distance from the object to the center of the working space by adding a high-precision industrial camera and identifying through the camera h , and feeds it to the fuzzy controller, and outputs , and , and an adjustment algorithm is added to adjust the controller parameters of the controlled joints by using the joint speeds and accelerations of the parallel robot and the distance to the target object. This method can effectively reduce the influence of the coupling torque between joints on the tracking accuracy of the control system during high-speed movement. Compared with the traditional method, the advantage of the present invention is that when performing coupling adjustment, it is not necessary to accurately identify the mathematical model of the controlled object. At the same time, considering the coupling effect between joints and the pixel difference of the target object, the algorithm structure is simple, occupies less hardware resources, and is easy to implement. For example, the coupling gain adjustment method of the parallel robot based on visual recognition proposed in this application can be directly configured in a PID controller or a fuzzy controller to realize the adjustment of the controller parameters.

[0025] Specifically, as Figure 2 shown, it is a flowchart of the coupling gain adjustment method of the parallel robot based on visual recognition provided by an embodiment of this application. The coupling gain adjustment method of the parallel robot based on visual recognition includes the following steps S10 - S40.

[0026] S10: Obtain the position of the object and the position in the working space, and calculate the distance from the object to the center of the working space according to the position of the object and the position in the working space.

[0027] In this embodiment, the position of the object and the position in the working space can be obtained by setting a camera. For example, the camera first acquires the position of the object （x p ,y p ,z p ) and the position in the working space (x o ,y o ,z o )， Based on the acquired information, calculate the distance from the object to the working space h as and return the result to the operation process of the correction value to improve the control accuracy.

[0028] S20: Calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia.

[0029] In this embodiment, the inertia coupling index of each drive shaft in the joint space of the parallel robot ICI i , the inertia coupling index can be ICI iThe index value is defined between (0, 1), which is convenient for directly reflecting the inertia coupling strength of the mechanism; the larger the index value, the greater the coupling, and vice versa. Among them, the drive shaft in the joint space of the parallel robot can be the drive joint of the parallel robot. For example, the drive shaft includes the screw drive joint or the branch chain drive joint of the parallel robot.

[0030] In some embodiments, according to the self-load inertia of the drive shaft and the inter-axis coupling inertia, the inertia coupling index of each drive shaft is calculated by the following formula: ; In the formula, ICI i represents the inertia coupling index of the drive shaft, represents the coupling strength coefficient, e represents the base of the natural logarithm, M g ( i , j ) represents a symmetric positive definite matrix, including the self-load inertia of the drive shaft and the inter-axis coupling inertia, i represents the controlled joint, j represents the other joints except the controlled joint, and n represents the number of drive joints of the parallel robot.

[0031] In this embodiment, the symmetric positive definite matrix M g is expressed as: ; In the formula, J mm is the self-load inertia of the drive shaft, while J mk is the inter-axis coupling inertia, m and k are both the serial numbers of the drive shafts, m = 1, 2, 3, 4; k = 1, 2, 3, 4; and m ≠ k .

[0032] Parallel robots usually operate on high-speed and high-acceleration trajectories, and the motion and force coupling between their joints are particularly obvious in this case. The resulting disturbances will have a significant impact on the control performance and cannot be ignored. Therefore, according to the motion state of the robot, the initial value of the fuzzy adjustment amount of the controlled joint can be adjusted in real time through the following steps S30 and S40, so as to achieve the goal of anti-interference and improve the control accuracy.

[0033] S30: Set the speed threshold value and acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine the correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft.

[0034] Exemplarily, the parallel robot may include two screw drive joints and two branch chain drive joints, where the set speed threshold and acceleration threshold for each joint can have specific values that may be partially the same or completely different according to the actual situation. The speed and acceleration of each joint are compared with the set speed threshold and acceleration threshold of the corresponding joint to initiate the calculation of the correction value when the speed of the joint exceeds the speed threshold or the acceleration exceeds the acceleration threshold.

[0035] In some embodiments, for the controller parameters of the screw drive joint, it is determined that when and are satisfied, the fuzzy adjustment amount is not corrected; when or are satisfied, the correction value of the fuzzy adjustment amount is determined by the following formula: ; In the formula, represents the first correction value, and respectively represent the speed threshold and acceleration threshold of the corresponding joint of the parallel robot, and respectively represent the joint speed and acceleration of the parallel robot, h represents the distance from the object to the center of the workspace, represents the first correction factor, respectively take , , .

[0036] In some embodiments, for the controller parameters of the two branch chain drive joints, it is determined that when and are satisfied, the fuzzy adjustment amount is not corrected; when or are satisfied, the correction value of the fuzzy adjustment amount is determined by the following formula: ; In the formula, represents the second correction value, and respectively represent the speed threshold and acceleration threshold of the corresponding joint of the parallel robot, and respectively represent the joint speed and acceleration of the parallel robot, h represents the distance from the object to the center of the workspace, represents the second correction factor, respectively take , , .

[0037] S40: Determine the fuzzy adjustment amount of the controller parameters of the parallel robot based on the correction value.

[0038] In some embodiments, based on the first correction value, the fuzzy adjustment amount of the controller parameters of the lead screw drive joint of the parallel robot is determined by the following formula: ; ; ; In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the derivative parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the derivative parameter adjustment amount.

[0039] In some embodiments, based on the second correction value, the fuzzy adjustment amount of the controller parameters of the branch chain drive joint of the parallel robot is determined by the following formula: ; ; ; In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the derivative parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the derivative parameter adjustment amount.

[0040] Figure 3 is the control flow chart of a method for adjusting the coupling gain of a parallel robot based on visual recognition provided by an embodiment of the present application. As Figure 3 shown, the rotation angles of each joint are used as the input values of the trajectory, and preliminary interpolation is completed through the interpolation module. The result after interpolation is used to perform the inverse kinematics of the high-speed parallel robot through inverse kinematics, so as to obtain the target position commands of each joint, and these commands are used as the input of the servo control algorithm. Taking the inertia coupling index ICIiAs the input of correction coefficients (including two-branch correction coefficients and two-screw rod correction coefficients). Meanwhile, the following errors and and the error change rate ec collected in real time by each joint control system are used as the inputs of the controller, and the fuzzy adjustment amounts , , are calculated. The speeds and accelerations of each joint are judged through thresholds to determine whether to call the correction values calculated in step S30. If called, S40 is executed to calculate the final fuzzy adjustment amount. Finally, the servo control algorithm updates the controller parameters according to the fuzzy adjustment amount and generates the final actual angle output.

[0041] In this embodiment, the following error e t , the error change rate e c , the distance from the object to the workspace h , the fuzzy adjustment amounts , , , the speeds and accelerations of each joint, and the threshold values and are all defined as global variables to facilitate the high-speed reading and writing of these data.

[0042] In summary, a method for adjusting the coupling gain of a parallel robot based on visual recognition proposed in this application is based on the traditional fuzzy feedback control strategy, adds a vision system and correction coefficients, and adjusts the fuzzy correction amount of the controller parameters by considering the coupling effect between joints. The advantages of this application are that when performing fuzzy correction, there is no need to accurately identify the mathematical model of the controlled object, and at the same time, considering the coupling effect between joints and the pixel difference of the target object, the algorithm structure is simple, the hardware resources occupied are less, and it is easy to implement.

[0043] This application embodiment also provides a device for adjusting the coupling gain of a parallel robot based on visual recognition. As shown in Figure 4 , the device for adjusting the coupling gain of a parallel robot based on visual recognition includes: A vision processing module 401, configured to obtain the position of the object and the position of the workspace, and calculate the distance from the object to the center of the workspace according to the position of the object and the position of the workspace; A coupling index calculation module 402, configured to calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia; The correction value calculation module 403 is configured to set the speed threshold value and acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, a correction value is determined according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; The adjustment amount calculation module 404 is configured to determine a fuzzy adjustment amount of the controller parameters of the parallel robot based on the correction value.

[0044] In some embodiments, the vision processing module is further configured to calculate the distance from the object to the center of the working space according to the position of the object and the position of the working space h as: ; In the formula, x p , y p , z p are the position coordinates of the object respectively, x o , y o , z o are the position coordinates of the working space respectively.

[0045] In some embodiments, the coupling index calculation module is further configured to calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia through the following formula: ; In the formula, ICI i represents the inertia coupling index of the drive shaft, represents the coupling strength coefficient, e represents the base of the natural logarithm, M g ( i , j ) represents a symmetric positive definite matrix, including the self-load inertia of the drive shaft and the inter-axis coupling inertia, i represents the controlled joint, j represents the other joints except the controlled joint, and n represents the number of drive joints of the parallel robot.

[0046] In some embodiments, the joints of the parallel robot include screw drive joints, and the correction value calculation module is further configured to determine a first correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft when the speed of the screw drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, by the following formula: ; In the formula, represents the first correction value, and respectively represent the speed threshold value and the acceleration threshold value of the corresponding joint of the parallel robot, and respectively represent the joint speed and acceleration of the parallel robot, h represents the distance from the object to the center of the working space, represents the first correction factor.

[0047] In some embodiments, the adjustment amount calculation module is further configured to determine a fuzzy adjustment amount of the controller parameters of the screw drive joints of the parallel robot based on the first correction value, by the following formula: ; ; ; In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the differential parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the differential parameter adjustment amount.

[0048] In some embodiments, the joints of the parallel robot include chain drive joints, and the correction value calculation module is further configured to determine a second correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft when the speed of the chain drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, by the following formula: ; In the formula, represents the second correction value, and respectively represent the speed threshold value and the acceleration threshold value of the corresponding joint of the parallel robot, and They represent the joint velocity and acceleration of the parallel robot, h Represents the distance from the object to the center of the workspace, Represents the second correction factor.

[0049] In some embodiments, the adjustment amount calculation module is further configured to determine the fuzzy adjustment amount of the controller parameter of the branched chain driving joint of the parallel robot based on the second correction value by the following formula: ; ; ; In the formula, Indicates the initial value of the proportional parameter adjustment output by the fuzzy controller, Indicates the initial value of the integral parameter adjustment output by the fuzzy controller, Represents the initial value of the differential parameter adjustment output by the fuzzy controller, , and They represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the differential parameter adjustment amount respectively.

[0050] An embodiment of the present application provides an electronic device, which may include: a processor and a memory, wherein the processor and the memory may communicate with each other; illustratively, the processor and the memory communicate with each other via a communication bus.

[0051] The processor executes the computer execution instructions stored in the memory, so that the processor executes the scheme in the above embodiment. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components.

[0052] The communication bus can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus can be divided into an address bus, a data bus, a control bus, etc. The transceiver is used to implement communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include Random Access Memory (RAM) and may also include non-volatile memory.

[0053] The electronic device provided by the embodiments of the present application can be the terminal device of the above embodiments.

[0054] The embodiments of the present application also provide a computer-readable storage medium. Computer instructions are stored in the computer-readable storage medium. When the computer instructions run on a computer, the computer is enabled to execute the technical solutions of the method for adjusting the coupling gain of a parallel robot based on visual recognition in the above embodiments.

[0055] The embodiments of the present application also provide a computer program product. The computer program product includes a computer program which is stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, the technical solutions of the method for adjusting the coupling gain of a parallel robot based on visual recognition in the above embodiments can be implemented.

[0056] In the several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or modules can be in electrical, mechanical, or other forms.

[0057] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to implement the solutions of this embodiment.

[0058] In addition, in each embodiment of the present application, each functional module can be integrated into a processing unit, or each module can exist physically alone, or two or more modules can be integrated into one unit. The unit formed by the above modules can be implemented in the form of hardware, or in the form of a hardware plus software functional unit.

[0059] The integrated module implemented in the form of a software functional module can be stored in a computer-readable storage medium. The above software functional module is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods in the embodiments of the present application.

[0060] It should be understood that the above processor can be a central processing unit (Central Processing Unit, abbreviated as CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, abbreviated as DSP), application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly embodied as being executed and completed by a hardware processor, or by a combination of hardware and software modules in the processor.

[0061] The memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory, and can also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk, or an optical disc, etc.

[0062] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0063] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0064] An exemplary storage medium is coupled to the processor, enabling the processor to read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a master control device.

[0065] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes various media that can store program codes, such as ROM, RAM, magnetic disk or optical disk.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for adjusting the coupling gain of a parallel robot based on visual recognition, characterized in that The method includes: Obtaining the position of an object and the position of the working space, and calculating the distance from the object to the center of the working space according to the position of the object and the position of the working space; Calculating the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia; Setting the speed threshold value and the acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determining a correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; Based on the correction value, determining the fuzzy adjustment amount of the controller parameters of the parallel robot.

2. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 1, wherein Calculate the distance from the object to the center of the working space according to the position of the object and the position of the working space h It is: ； Wherein, x p , y p , z p are respectively the position coordinates of the object, x o , y o , z o are respectively the position coordinates of the workspace.

3. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 1, wherein According to the self-load inertia of the drive shaft and the inter-axis coupling inertia, calculate the inertia coupling index of each drive shaft through the following formula: ； In the formula, ICI i represents the inertia coupling index of the drive shaft, represents the coupling strength coefficient, e represents the base of the natural logarithm, M g ( i , j ) represents a symmetric positive definite matrix, including the self-load inertia of the drive shaft and the inter-axis coupling inertia, i represents the controlled joint, j represents the other joints except the controlled joint, and n represents the number of drive joints of the parallel robot.

4. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 3, characterized in that, The joint of the parallel robot includes a lead screw drive joint. When the speed of the lead screw drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine the first correction value through the following formula according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; ； Wherein, represents the first correction value, and respectively represent the speed threshold value and the acceleration threshold value of the corresponding joints of the parallel robot, and respectively represent the joint speed and the acceleration of the parallel robot, h represents the distance from the object to the center of the working space, represents the first correction factor.

5. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 4, wherein Based on the first correction value, determine the fuzzy adjustment amount of the controller parameters of the lead screw drive joint of the parallel robot through the following formula: ； ； ； Wherein, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the differential parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the differential parameter adjustment amount.

6. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 5, characterized in that, The joint of the parallel robot includes a branch chain drive joint. When the speed of the branch chain drive joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine the second correction value through the following formula according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; ； In the formula, represents the second correction value, and respectively represent the speed threshold value and the acceleration threshold value of the corresponding joint of the parallel robot, and respectively represent the joint speed and acceleration of the parallel robot, h represents the distance from the object to the center of the working space, represents the second correction factor.

7. The method for adjusting the coupling gain of a parallel robot based on visual recognition according to claim 6, wherein Based on the second correction value, determine the fuzzy adjustment amount of the controller parameters of the branch chain drive joint of the parallel robot through the following formula: ； ； ； In the formula, represents the initial value of the proportional parameter adjustment amount output by the fuzzy controller, represents the initial value of the integral parameter adjustment amount output by the fuzzy controller, represents the initial value of the derivative parameter adjustment amount output by the fuzzy controller, , and respectively represent the correction values of the proportional parameter adjustment amount, the integral parameter adjustment amount, and the derivative parameter adjustment amount.

8. A coupling gain adjustment device for a parallel robot based on visual recognition, characterized in that, The device includes: A vision processing module configured to obtain the position of an object and the position of the working space, and calculate the distance from the object to the center of the working space according to the position of the object and the position of the working space; A coupling index calculation module configured to calculate the inertia coupling index of each drive shaft according to the self-load inertia of the drive shaft and the inter-axis coupling inertia; A correction value calculation module configured to set the speed threshold value and the acceleration threshold value of each joint of the parallel robot. When the speed of the joint exceeds the speed threshold value or the acceleration exceeds the acceleration threshold value, determine a correction value according to the distance from the object to the center of the working space and the inertia coupling index of the drive shaft; An adjustment amount calculation module configured to determine the fuzzy adjustment amount of the controller parameters of the parallel robot based on the correction value.

9. An electronic device, characterized in that, Includes: A processor, and a memory communicatively connected to the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method for adjusting the coupling gain of a parallel robot based on visual recognition according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium. When the computer execution instructions are executed by a processor, they are used to implement the method for adjusting the coupling gain of a parallel robot based on visual recognition according to any one of claims 1-7.

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