Tight fit shaft hole assembly method, system, electronic device, and storage medium

Abstract

This invention provides a method, system, electronic device, and storage medium for robot tight-fitting shaft hole assembly, relating to the field of robot automated assembly technology. The tight-fitting shaft hole assembly method uses a robotic arm end effector to fix and grip the shaft. The method includes: obtaining the posture of the robotic arm end effector and a six-dimensional force / torque ELM network; obtaining the six-dimensional force / torque of the robotic arm end effector at the current moment; obtaining the posture of the robotic arm end effector at the next moment based on the six-dimensional force / torque of the robotic arm end effector at the current moment and the ELM network; determining whether the posture of the robotic arm end effector at the next moment is less than a preset threshold; if it is greater, adjusting the posture of the robotic arm end effector at the current moment to the posture of the robotic arm end effector at the next moment, and repeating the above actions; if it is less, completing the assembly action. This invention improves the success rate of robot tight-fitting shaft hole assembly by establishing an ELM network.

Description

Technical Field

[0001] This invention relates to the field of robotic automated assembly technology, and in particular to a robot tight-fitting shaft hole assembly method, system, electronic device and storage medium. Background Technology

[0002] Shaft-hole assembly is a mechanical assembly process used to insert one component (usually a shaft or pin) into another component (usually a hole or sleeve) to achieve connection or transmission between them. Shaft-hole assembly is a common operation in manufacturing processes and is widely used in various industries and products, including automotive manufacturing, machining, and electronic equipment assembly. To save labor and increase the automation level of production, robotic systems are now commonly used to automate shaft-hole assembly.

[0003] In existing technologies, robots typically use vision systems to extract the position of shaft holes, thereby achieving shaft-hole assembly. During the assembly process, when the robot grasps the shaft / inserts it into the shaft hole, there is often a misalignment between the shaft and the shaft hole. If the inner diameter of the shaft hole is larger than the diameter of the shaft, there is still a relatively high probability that assembly can be achieved. However, for products such as USB and network cable ports, the shaft and shaft hole need to fit tightly (the inner diameter of the shaft hole is equal to or slightly smaller than the shaft diameter). If there is a misalignment between the shaft and the shaft hole, successful assembly is difficult and may even damage the shaft and the joints of the robot arm. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method, system, electronic device, and storage medium for tight-fitting shaft and hole assembly. By establishing an ELM network, the success rate of robot tight-fitting shaft and hole assembly is improved. The technical solution is as follows:

[0005] This invention specifically provides a tight-fitting shaft hole assembly method, in which the end effector of a robotic arm is used to fix and grip the shaft. The method includes: obtaining the posture of the end effector of the robotic arm and a six-dimensional force / torque ELM network; obtaining the six-dimensional force / torque of the end effector of the robotic arm at the current moment; obtaining the posture of the end effector of the robotic arm at the next moment based on the six-dimensional force / torque of the end effector of the robotic arm at the current moment and the ELM network; determining whether the posture of the end effector of the robotic arm at the next moment is less than a preset threshold; if it is greater, adjusting the posture of the end effector of the robotic arm at the current moment to the posture of the end effector of the robotic arm at the next moment, and repeating the above actions; if it is less, completing the assembly action.

[0006] Furthermore, the ELM network for obtaining the posture and six-dimensional force / torque of the robotic arm end effector specifically includes: controlling the robotic arm to complete the tight-fitting shaft hole assembly multiple times, and recording multiple sets of posture data and corresponding six-dimensional force / torque data of the robotic arm end effector during the assembly process; and constructing and training all parameters of the ELM network based on the ELM algorithm according to the multiple sets of posture data and corresponding six-dimensional force / torque data of the robotic arm end effector.

[0007] Furthermore, the construction formula for the ELM network is as follows:

[0008]

[0009] Where β i ,w i ,b i is the parameter, and g(.) is the activation function.

[0010] Furthermore, the objective function of the ELM network is:

[0011]

[0012] Where H = W T X+B, where T represents the posture corresponding to each set of six-dimensional forces / torques.

[0013] Furthermore, the method also includes: obtaining a mapping network between the velocity of the robotic arm end effector and a six-dimensional force / torque; obtaining the velocity of the robotic arm end effector at the next moment based on the six-dimensional force / torque of the robotic arm end effector at the current moment and the mapping network; repeating the above actions until the posture of the robotic arm end effector at the next moment is less than a preset threshold.

[0014] Furthermore, the process of obtaining the mapping network between the speed of the robotic arm end effector and the six-dimensional force / torque specifically includes: classifying the six-dimensional force / torque according to its numerical value, with each category of six-dimensional force / torque corresponding to a set of speed parameters of the robotic arm end effector.

[0015] The present invention also provides a tight-fitting shaft and hole assembly system, the system comprising: a data acquisition module for acquiring six-dimensional force / torque data in the current state; an assembly assistance module for inputting the six-dimensional force / torque data into an ELM network to obtain the corresponding posture of the robotic arm end effector; and a workpiece assembly module for changing the posture of the robotic arm end effector to complete the shaft and hole assembly work.

[0016] Furthermore, the assembly assistance module is also used to input six-dimensional force / torque data into the mapping network to obtain the corresponding speed of the robotic arm end effector; the workpiece assembly module is also used to change the speed of the robotic arm end effector to complete the shaft hole assembly work.

[0017] The present invention also specifically provides an electronic device, comprising: at least one processor, at least one memory, and at least one communication bus, wherein the memory stores a computer program, and the processor reads the computer program in the memory through the communication bus; when the computer program is executed by the processor, it implements the above-described tight-fitting shaft hole assembly method.

[0018] The present invention also specifically provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described tight-fitting shaft hole assembly method.

[0019] The beneficial effects of this invention are:

[0020] First, the tight-fitting shaft and hole assembly method of this invention establishes an ELM network between posture and six-dimensional force / torque based on the ELM algorithm. When posture deviation occurs, the robot can promptly adjust back to the correct direction according to the ELM network. This method is applicable to tight-fitting shaft and hole assembly such as USB and network cable ports, with a high success rate and reduced damage to the shaft to be assembled or the joints of the robot arm. Furthermore, this embodiment uses the ELM algorithm, which improves efficiency and accuracy, has strong generalization performance (effectively applied to different workpieces), and is more intelligent.

[0021] Secondly, the assembly method in this invention also utilizes PID control to control the speed of the robotic arm. A variable-parameter PID control mapping network model is introduced, selecting different PID parameters based on different six-dimensional forces / torques to ultimately control the movement speed of the robotic arm's end effector. By changing the PID parameters according to the six-dimensional forces / torques, the movement speed of the robotic arm's end effector is changed in real time, making the assembly process more human-like and smoother. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below.

[0023] Figure 1 This is a schematic diagram illustrating the implementation environment involved in this application according to an exemplary embodiment;

[0024] Figure 2 This is a flowchart illustrating a tight-fitting shaft-hole assembly method according to an exemplary embodiment;

[0025] Figure 3 This is a flowchart illustrating step 310 according to an exemplary embodiment;

[0026] Figure 4 This is a flowchart illustrating an application scenario according to an exemplary embodiment;

[0027] Figure 5This is a structural block diagram illustrating a tight-fitting shaft-hole assembly system according to an exemplary embodiment;

[0028] Figure 6 This is a hardware structure diagram of an electronic device according to an exemplary embodiment;

[0029] Figure 7 This is a structural block diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar components or components having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0031] In the description of this specification, the terms "Embodiment 1," "this embodiment," or "in one embodiment," etc., indicate that the specific features, structures, materials, or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example; moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in one or more embodiments or examples.

[0032] In the description of this specification, the terms "connection," "installation," "fixing," "setting," and "having" are interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0033] In the description of this specification, relational terms such as “first” and “second” are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0034] While existing technologies can achieve rapid shaft-hole assembly, most rely heavily on precise vision technology. Furthermore, the assembly tasks they address typically involve holes larger than shaft diameters, thus failing to consider tight fits. Additionally, uncertainties in the robotic arm's end effector during workpiece grasping or assembly can lead to posture deviations. Existing technologies propose a teaching-based learning method, but it uses a probabilistic model and has poor adaptability to different environments. Another proposed method is reinforcement learning, but reinforcement learning suffers from long training times, susceptibility to local optima, and the need to learn in a simulation environment before transferring to the real world. Since the parameters in simulation and real environments differ, this results in significant errors.

[0035] It is evident that in the existing technology, when assembling a tight-fitting shaft and hole, if there is an attitude shift between the shaft and the hole, it is difficult to assemble successfully and may damage the shaft and the joints of the robot arm.

[0036] Therefore, this application provides a tight-fitting shaft hole assembly method, which can adjust the posture of the end of the robotic arm that grips the shaft to be assembled. Accordingly, the tight-fitting shaft hole assembly method is applicable to a tight-fitting shaft hole assembly system, which can be deployed in an industrial robot.

[0037] Figure 1 This is a schematic diagram of the implementation environment involved in a tight-fitting shaft-hole assembly method. The implementation environment includes a robotic arm 1, a six-dimensional force / torque sensor 2, a two-finger gripper 3, a shaft to be assembled 4, and a shaft hole 5.

[0038] Specifically, the robotic arm is a multi-axis robotic arm with motion control functions. A two-finger gripper is installed at the end of the robotic arm, and a six-dimensional force / torque sensor is installed between the robotic arm and the two-finger gripper. The six-dimensional force / torque sensor is used to measure the force / torque data in each direction of the robotic arm. The robotic arm can be a UR5 robotic arm. The two-finger gripper 3 grasps the shaft 4 to be assembled and assembles it into the shaft hole 5.

[0039] Please see Figure 2 This application provides a method for assembling a tight-fitting shaft hole, wherein the end of a robotic arm is used to fix and grip the shaft, and the method may include the following steps:

[0040] Step 310: Obtain the pose of the robotic arm end effector and the six-dimensional force / torque ELM network.

[0041] In one possible implementation, such as Figure 3 As shown, the ELM network for obtaining the posture and six-dimensional force / torque of the robotic arm end effector includes the following steps;

[0042] Step 311: The human instructor controls the robotic arm to complete the tight-fitting shaft hole assembly multiple times, and records the posture data of the robotic arm end and the corresponding six-dimensional force / torque data during the assembly process.

[0043] Specifically, the UR5 robotic arm is connected via TCP communication, and the real-time status of the end effector, including position, orientation, and six-dimensional force / torque data, is recorded using ROS packages. After the code is started, a human instructor drags the robotic arm into the hole, collecting nine trajectories. The recorded data is then filtered and saved to a text file.

[0044] Step 312: Based on multiple sets of posture data of the robotic arm end effector and the corresponding six-dimensional force / torque data, construct and train the ELM network to obtain all parameters of the ELM network.

[0045] In one exemplary embodiment, the construction formula for the ELM network is as follows:

[0046]

[0047] Where β i ,w i ,b i The parameter is g(.), and the activation function is the Sigmoid function. The six-dimensional force / torque data is mapped from its original spatial form to the feature space of the ELM, transforming it into matrix form as follows:

[0048] Hβ=O

[0049] Where H = W T X+B.

[0050] In an exemplary embodiment, the objective function of the ELM network is:

[0051]

[0052] T represents the posture corresponding to each group of six-dimensional forces / torques.

[0053] When training the network, we randomize w i ,b i Therefore, only the parameter β needs to be determined. i

[0054]

[0055] in We use H as the pseudo-inverse matrix, and then train the network using the six-dimensional force / torque data in the training set as input to obtain all the parameters of the network.

[0056] Step 320: Obtain the six-dimensional force / torque at the end of the robotic arm at the current moment.

[0057] In one possible implementation, through, as Figure 1 The six-dimensional force / torque sensor shown acquires force / torque data in each direction of the robotic arm.

[0058] Step 330: Based on the six-dimensional force / torque at the end of the robotic arm at the current moment and the ELM network, obtain the posture of the end of the robotic arm at the next moment.

[0059] Specifically, when the two-finger gripper grasps the shaft to be assembled, a posture deviation occurs. If the assembly method is followed normally, it may damage the shaft to be assembled. The six-dimensional force / torque at the end of the robotic arm at the current moment is input into the trained ELM network to obtain the posture of the end of the robotic arm at the next moment. The robotic arm adjusts its angle according to this posture at the next moment.

[0060] Step 340: Determine whether the end position of the robotic arm at the next moment is less than a preset threshold. If it is greater than the threshold, adjust the end position of the robotic arm at the current moment to the end position of the robotic arm at the next moment and repeat the above action. If it is less than the threshold, complete the assembly action.

[0061] With repeated adjustments, the shaft to be assembled will eventually be adjusted to the correct posture. At this point, since there is no posture deviation, the posture output by the ELM network based on the input six-dimensional force / torque will be relatively small. When the posture is less than the threshold, the assembly can be determined to be successful.

[0062] The tight-fitting shaft and hole assembly method in this embodiment establishes an ELM network between posture and six-dimensional force / torque based on the ELM algorithm. When posture deviation occurs, the robot can promptly adjust back to the correct orientation according to the ELM network. This method is applicable to tight-fitting shaft and hole assembly such as USB and network cable ports, with a high success rate and reduced damage to the shaft to be assembled or the joints of the robot arm. Furthermore, the use of the ELM algorithm in this embodiment improves efficiency and accuracy, has strong generalization performance (effectively applied to different workpieces), and is more intelligent.

[0063] In one embodiment, a tight-fitting shaft-hole assembly method is provided.

[0064] Step 310 also includes: obtaining a mapping network between the velocity of the robotic arm end effector and the six-dimensional force / torque.

[0065] In one possible implementation, the six-dimensional forces / torques are classified according to their numerical values, with each category of six-dimensional forces / torques corresponding to a set of velocity parameters at the end of the robotic arm.

[0066] Step 330 further includes: obtaining the speed of the robotic arm's end effector at the next moment based on the six-dimensional force / torque at the current moment and the mapping network. Specifically, as the workpiece penetrates deeper into the hole, the six-dimensional force / torque increases, and within a certain range of six-dimensional force / torque, the robotic arm's movement speed will correspondingly increase. When the assembly task is nearing success, the six-dimensional force / torque will be in a larger range, at which point the corresponding speed of the robotic arm's end effector decreases, and the robotic arm speed slows down. A PID controller (Proportional-Integral-Derivative) can be used to control the robotic arm's movement speed; different PID parameters are selected based on different six-dimensional forces / torques to ultimately control different robotic arm movement speeds.

[0067] Step 340 further includes: repeating the above actions until the posture of the robotic arm end is less than a preset threshold posture and the robotic arm speed is zero.

[0068] The assembly method in this embodiment utilizes PID control to control the speed of the robotic arm. A variable-parameter PID control mapping network model is introduced, selecting different PID parameters based on different six-dimensional forces / torques to ultimately control the movement speed of the robotic arm's end effector. By changing the PID parameters according to the six-dimensional forces / torques, the movement speed of the robotic arm's end effector is changed in real time, making the assembly process more human-like and smoother.

[0069] In one possible implementation, Figure 1 Taking the implementation environment shown as an example, such as Figure 4 The diagram shows the assembly process of a tight-fitting shaft and hole in a practical application scenario.

[0070] Specifically, in the preparatory stage, firstly, human instructors collect data, and then train the network based on the collected data to obtain PID parameters and ELM network parameters, thus obtaining the ELM network and the variable parameter PID control mapping network.

[0071] The camera acquires the positions of the shaft and the shaft hole to be assembled, initializes the hole position, and then moves the robotic arm to the target (the object to be assembled), with the gripper grasping the object (shaft). A six-dimensional sensor obtains the current force data and inputs it into the ELM network and the variable-parameter PID control mapping network of the robotic arm's end effector, mapping the speed to the six-dimensional force / torque. The system then outputs attitude and position velocity to control the robotic arm's movement. The system checks if the output attitude is below a threshold; if it is, the above steps are repeated; otherwise, the assembly task ends.

[0072] The following are system embodiments of this application, which can be used to execute the tight-fitting shaft hole assembly method involved in this application. For details not disclosed in the device embodiments of this application, please refer to the method embodiments of the tight-fitting shaft hole assembly method involved in this application.

[0073] Please see Figure 5 This application provides a tight-fitting shaft hole assembly system 600, including but not limited to a data acquisition module 610, an assembly auxiliary module 620, and a workpiece assembly module 630.

[0074] The data acquisition module 610 is used to acquire six-dimensional force / torque data under the current state.

[0075] Assembly assistance module 620 is used to input six-dimensional force / torque data into the ELM network to obtain the corresponding posture of the robotic arm end effector;

[0076] The workpiece assembly module 630 is used to change the posture of the end effector of the robotic arm to complete the shaft hole assembly work.

[0077] In one possible implementation, the data acquisition module 610, through, as... Figure 1 The six-dimensional force / torque sensor shown acquires force / torque data in each direction of the robotic arm.

[0078] In one exemplary embodiment, the assembly assistance module 620 is further configured to input six-dimensional force / torque data into a mapping network to obtain the corresponding speed of the robotic arm end effector;

[0079] The workpiece assembly module 630 is also used to change the speed of the end effector of the robotic arm to complete the shaft hole assembly work.

[0080] It should be noted that the tight-fitting shaft hole assembly system provided in the above embodiments is only illustrated by the division of the above functional modules when assembling shaft holes. In actual applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the tight-fitting shaft hole assembly system will be divided into different functional modules to complete all or part of the functions described above.

[0081] Furthermore, the tight-fitting shaft hole assembly system and tight-fitting shaft hole assembly method provided in the above embodiments belong to the same concept. The specific way each module performs its operation has been described in detail in the method embodiments, and will not be repeated here.

[0082] An electronic device includes: at least one processor, at least one memory, and at least one communication bus, wherein the memory stores a computer program, and the processor reads the computer program from the memory via the communication bus; when the computer program is executed by the processor, it implements the above-mentioned tight-fitting shaft hole assembly method.

[0083] Figure 6 A schematic diagram of the structure of an electronic device is shown according to an exemplary embodiment.

[0084] It should be noted that this electronic device is merely an example adapted to this application and should not be construed as providing any limitation on the scope of use of this application. Furthermore, this electronic device should not be interpreted as requiring or depending on any specific feature. Figure 6 One or more components of the exemplary electronic device 2000 shown.

[0085] The hardware structure of electronic devices 2000 can vary significantly due to differences in configuration or performance, such as... Figure 6 As shown, the electronic device 2000 includes: a power supply 210, an interface 230, at least one memory 250, and at least one central processing unit (CPU) 270.

[0086] Specifically, power supply 210 is used to provide operating voltage for various hardware devices on electronic device 2000.

[0087] Interface 230 includes at least one wired or wireless network interface 231 for interacting with external devices.

[0088] Of course, in other examples adapted in this application, interface 230 may further include at least one serial-to-parallel conversion interface 233, at least one input / output interface 235, and at least one USB interface 237, etc. Figure 6 As shown, this does not constitute a specific limitation.

[0089] The memory 250 serves as a carrier for resource storage and can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it include the operating system 251, application programs 253, and data 255, etc., and the storage method can be temporary storage or permanent storage.

[0090] The operating system 251 is used to manage and control the various hardware devices and application programs 253 on the electronic device 2000, so as to enable the central processing unit 270 to perform calculations and processing on the massive data 255 in the memory 250. It can be Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0091] Application 253 is a computer program that performs at least one specific task based on operating system 251, and may include at least one module ( Figure 6 (Not shown), each module can contain a computer program for the electronic device 2000.

[0092] The central processing unit 270 may include one or more processors and is configured to communicate with the memory 250 via at least one communication bus to read computer programs stored in the memory 250, thereby enabling the calculation and processing of massive amounts of data 255 in the memory 250.

[0093] Furthermore, this application can also be implemented through hardware circuits or a combination of hardware circuits and software. Therefore, the implementation of this application is not limited to any specific hardware circuit, software, or combination thereof.

[0094] Please see Figure 7 This application provides an electronic device 4000.

[0095] exist Figure 7 The electronic device 4000 includes at least one processor 4001, at least one communication bus 4002, and at least one memory 4003.

[0096] The processor 4001 and memory 4003 are connected, for example, via a communication bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of this application.

[0097] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0098] The communication bus 4002 may include a path for transmitting information between the aforementioned components. The communication bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0099] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0100] The memory 4003 stores a computer program, and the processor 4001 reads the computer program stored in the memory 4003 through the communication bus 4002.

[0101] When the computer program is executed by the processor 4001, it implements the tight-fitting shaft hole assembly method in the above embodiments.

[0102] Furthermore, this application provides a storage medium storing a computer program, which, when executed by a processor, implements the tight-fitting shaft hole assembly method described in the above embodiments.

[0103] This application provides a computer program product, which includes a computer program stored in a storage medium. A processor of a computer device reads the computer program from the storage medium and executes the computer program, causing the computer device to perform the tight-fitting shaft-hole assembly method described in the above embodiments.

[0104] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0105] The above description of the embodiments is intended to enable those skilled in the art to understand and apply the technology of this invention. Those skilled in the art can easily make various modifications to these examples and apply the general principles described herein to other embodiments without creative effort. Therefore, this invention is not limited to the above embodiments. Modifications in the following situations should be within the scope of protection of this invention: ① New technical solutions implemented based on the technical solution of this invention and combined with existing common knowledge, where the technical effects of the new technical solution do not exceed the technical effects of this invention; ② Equivalent substitutions of some features of the technical solution of this invention using known technology, resulting in the same technical effects as those of this invention; ③ Extendable technical solutions based on the technical solution of this invention, where the substantive content of the extended technical solution does not exceed the technical solution of this invention; ④ Equivalent transformations made using the content of this specification and drawings, directly or indirectly applied to other related technical fields.

Claims

1. A method for assembling a tight-fitting shaft hole, wherein the end of a robotic arm is used to fix and grip a shaft, and the tight-fitting shaft hole assembly is an assembly in which the inner diameter of the shaft hole is equal to or slightly smaller than the shaft diameter, characterized in that, The method includes: Step 310: Obtain the posture and six-dimensional force / torque ELM network of the robotic arm end effector; specifically including: controlling the robotic arm to complete the tight-fitting shaft hole assembly multiple times, and recording multiple sets of posture data and corresponding six-dimensional force / torque data of the robotic arm end effector during the assembly process; based on the multiple sets of posture data and corresponding six-dimensional force / torque data of the robotic arm end effector, constructing and training the ELM network based on the ELM algorithm to obtain all parameters of the ELM network; Obtain the variable parameter PID control mapping network between the speed of the robotic arm end effector and the six-dimensional force / torque, specifically including: different six-dimensional forces / torques correspond to different PID parameters, and the PID parameters are changed according to the six-dimensional force / torque to change the motion speed of the robotic arm end effector in real time; Step 320: Obtain the six-dimensional force / torque at the end of the robotic arm at the current moment; Step 330: Based on the six-dimensional force / torque at the end of the robotic arm at the current moment and the ELM network, obtain the posture of the end of the robotic arm at the next moment; based on the six-dimensional force / torque at the end of the robotic arm at the current moment and the variable parameter PID control mapping network, obtain the velocity of the end of the robotic arm at the next moment. Step 340: Determine whether the posture of the robotic arm end effector at the next moment is less than a preset threshold. If it is greater than a preset threshold, adjust the posture of the robotic arm end effector at the current moment to the posture of the robotic arm end effector at the next moment, and control the robotic arm to move at the speed of the robotic arm end effector at the next moment. Then repeat steps 320 to 340. If it is less than a preset threshold, complete the assembly action.

2. The tight-fitting shaft hole assembly method as described in claim 1, characterized in that, The formula for constructing the ELM network is as follows: in For parameters, This is the activation function.

3. A tight-fitting shaft hole assembly system, used to perform the tight-fitting shaft hole assembly method according to any one of claims 1-2, characterized in that, The system includes: The data acquisition module is used to acquire six-dimensional force / torque data under the current state; The assembly assistance module is used to input six-dimensional force / torque data into the ELM network to obtain the corresponding posture of the robotic arm end effector; The workpiece assembly module is used to change the posture of the robotic arm's end effector to complete the shaft hole assembly work. The assembly assistance module is also used to input six-dimensional force / torque data into a mapping network to obtain the corresponding speed of the robotic arm end effector; The workpiece assembly module is also used to change the speed of the end effector of the robotic arm to complete the shaft hole assembly work.

4. An electronic device, characterized in that, include: At least one processor, at least one memory, and at least one communication bus, wherein, The memory stores a computer program, and the processor reads the computer program from the memory via the communication bus; When the computer program is executed by the processor, it implements the tight-fitting shaft hole assembly method according to any one of claims 1 to 2.

5. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the tight-fitting shaft hole assembly method as described in any one of claims 1 to 2.

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