WO2020135608A1

WO2020135608A1 - Industrial robot demonstration track recurrence method and system and robot

Info

Publication number: WO2020135608A1
Application number: PCT/CN2019/128774
Authority: WO
Inventors: 林炯辉; 朗需林; 刘培超; 曹林攀; 林俊凯
Original assignee: 深圳市越疆科技有限公司
Priority date: 2018-12-28
Filing date: 2019-12-26
Publication date: 2020-07-02
Also published as: CN109648571A

Abstract

The present application is applicable to the technical field of robots, and provided thereby are an industrial robot demonstration track recurrence method and system and a robot, the method comprising: collecting various joint information of a robot, and acquiring orientation information of a tail end orientation according to the various joint information of the robot; fitting the orientation information, and obtaining a continually recurring track; calculating the operating speed of the recurring track according to the recurring track; planning the speed of the recurring track according to the motion speed of the recurring track; and obtaining position information of the recurring track in each interpolation period according to a speed planning result, and controlling the robot to move according to the position information. Thus, the joint information of the robot is collected, fitting is carried out according to wave-filtered orientation information, and a continually recurring track is thus obtained, which reduces errors in the tail end orientation and simultaneously guarantees that the curvature of the recurring track is continuous. The speed of the generated recurring track is planned, so as to guarantee that the speed in the track recurring process is controllable.

Description

Industrial robot teaching trajectory reproduction method, system and robot

Technical field

The invention belongs to the technical field of robots, and in particular relates to a method, system and robot for teaching trajectory reproduction of industrial robots.

Background technique

At present, the application scope of industrial robots continues to expand, from various traditional application scenarios such as automobile manufacturing, electronic assembly, food processing, etc., and gradually penetrates into emerging fields such as consumer and service, which puts a higher priority on the ease of use and convenience of industrial robots. Claim.

Industrial robots generally determine desired target points and trajectories by teaching trajectories, and then trigger repeated execution of the trajectories taught according to external signals. The existing drag teaching trajectory reproduction method mainly includes: fitting the teaching trajectory in the joint space, and approximating the original teaching trajectory through polynomial interpolation. Or fit the teaching trajectory in Cartesian space and approach the original teaching trajectory through multiple small line segments. The above-mentioned trajectory obtained by joint space fitting has the problems of large robot terminal pose error and uncontrollable change of terminal pose speed. The above-mentioned trajectory obtained by multi-segment small-line segment fitting has discontinuous obtained trajectory, which requires many The smooth processing of the joints of the small line segments requires the smooth processing of the robot's terminal posture.

In summary, the current drag teaching trajectory reproduction method has the problems of large terminal pose error, uncontrollable change of pose speed, and discontinuous pose curve.

technical problem

In view of this, embodiments of the present invention provide a method, system and robot for teaching trajectory reproduction of industrial robots, to solve the current method of dragging teaching trajectory reproduction that has a large end pose error and an inaccurate change in pose velocity The problem of controlling and discontinuity of the pose curve.

Technical solution

The first aspect of the present invention provides a teaching trajectory reproduction method of an industrial robot, including:

Collect the joint information of the robot, obtain the posture information of the terminal posture according to the joint information of the robot, and filter the posture information;

Fit the posture information after filtering to obtain continuous recurring trajectories;

Calculating the running speed of the recurring trajectory according to the recurring trajectory;

Performing speed planning on the recurring trajectory according to the moving speed of the recurring trajectory;

The position information of each interpolation cycle of the recurring trajectory is obtained according to the speed planning result, and the robot is controlled to move according to the position information.

The second aspect of the present invention provides a teaching trajectory reproduction system of an industrial robot, including:

The posture information acquisition module is used to collect the joint information of the robot, obtain the posture information of the terminal posture according to the joint information of the robot, and filter the posture information;

The fitting module is used to fit the posture information after filtering to obtain a continuous recurring trajectory;

A speed calculation module, used to calculate the running speed of the recurring trajectory according to the recurring trajectory;

A speed planning module, configured to perform speed planning on the recurring trajectory according to the moving speed of the recurring trajectory;

The motion control module is used to obtain the position information of each interpolation cycle of the recurring trajectory according to the speed planning result, and control the robot to move according to the position information.

A third aspect of the present invention provides a robot including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the computer program to implement the following steps :

A fourth aspect of the present invention provides a computer-readable storage medium that stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

Beneficial effect

The method, system and robot for teaching trajectory reproduction of an industrial robot provided by the present invention collect the joint information of the robot, obtain posture information based on the joint information and perform filtering, and perform fitting based on the filtered posture information The obtained continuous recurring trajectory reduces the error of the end pose while ensuring the curvature of the recurring trajectory is continuous, and plans the speed of the generated recurring trajectory, thereby ensuring that the speed of the trajectory reproducing process is controllable, which effectively solves The current drag teaching trajectory reproduction method has the problems of large terminal pose error, uncontrollable change of pose speed, and discontinuous pose curve.

BRIEF DESCRIPTION

In order to more clearly explain the technical solutions in the embodiments of the present invention, the drawings required in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the invention. In some embodiments, for those of ordinary skill in the art, without paying creative labor, other drawings may be obtained based on these drawings.

1 is a schematic diagram of an implementation process of a method for reproducing a teaching trajectory of an industrial robot according to Embodiment 1 of the present invention;

2 is a schematic diagram of a pose curve of a method for teaching trajectory reproduction of an industrial robot according to Embodiment 1 of the present invention;

3 is a schematic flowchart of an implementation process corresponding to step S101 in Embodiment 1 provided by Embodiment 2 of the present invention;

4 is a schematic flowchart of an implementation process corresponding to step S102 in Embodiment 1 provided by Embodiment 3 of the present invention;

5 is a schematic flowchart of an implementation process corresponding to step S103 in Embodiment 1 provided by Embodiment 4 of the present invention;

6 is a schematic structural diagram of a teaching trajectory reproduction system of an industrial robot according to Embodiment 5 of the present invention;

FIG. 7 is a schematic structural diagram of a pose information acquisition module 101 corresponding to the fifth embodiment provided by the sixth embodiment of the present invention;

8 is a schematic structural diagram of the fitting module 102 in the fifth embodiment corresponding to the seventh embodiment of the present invention;

FIG. 9 is a schematic structural diagram of a speed calculation module 103 in Embodiment 5 corresponding to Embodiment 8 of the present invention;

10 is a schematic diagram of a terminal device provided in Embodiment 9 of the present invention.

Embodiments of the invention

In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are proposed to thoroughly understand the embodiments of the present invention. However, those skilled in the art should understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary details.

In order to explain the technical solution of the present invention, the following will be described with specific embodiments.

Example one:

As shown in FIG. 1, this embodiment provides a teaching trajectory reproduction method of an industrial robot, which specifically includes:

Step S101: Collect the joint information of the robot, acquire the posture information of the terminal posture according to the joint information of the robot, and filter the posture information.

In specific applications, drag the robot to produce a teaching trajectory, collect the information of each joint of the robot, and obtain the Cartesian pose information of the end through the positive solution of the robot kinematics. Filter the acquired pose information to eliminate the noise of pose information. Pose information includes position information and pose information. It should be noted that obtaining the Cartesian pose information of the terminal through the positive solution of the robot kinematics is an existing technology in the art, and will not be described in detail how to implement it here.

In specific applications, the information of each joint of the robot can be collected by sensors at each joint of the robot. It is also possible to collect information about each joint of the robot through an encoder installed at the robot joint or motor end, which is not limited.

Step S102: Fit the filtered posture information to obtain a continuous recurring trajectory.

In specific applications, the Nurbs curve is used to fit the pose information, and the Nurbs curve is used to fit to obtain a continuous recurring trajectory. As shown in FIG. 2, the Nurbs curve is used to fit the recurring trajectory to obtain a continuous posture curve. The above-mentioned posture curve is the reproducing trajectory.

In a specific application, fitting a Nurbs curve according to position information to obtain a continuous position curve, and fitting a Nurbs curve according to attitude information to obtain a continuous attitude curve.

Step S103: Calculate the running speed of the recurring trajectory according to the recurring trajectory.

In a specific application, the total length of the continuous position curve is calculated according to the continuous position curve in the recurring trajectory, and the operation of the recurring track is calculated according to the total motion duration of the dragging robot and the total length of the continuous position curve speed.

Step S104: Perform speed planning on the recurring trajectory according to the moving speed of the recurring trajectory.

In specific applications, the S-shaped speed curve is used for speed planning based on the calculated total length of the continuous position curve of the recurring trajectory and the calculated running speed of the recurring trajectory. It should be noted that the use of the S curve for speed planning is an existing technology in the art, and this embodiment will not repeat how to use the S-shaped speed curve for speed planning.

Step S105: Acquire position information of each interpolation cycle of the recurring trajectory according to the speed planning result, and control the robot to move according to the position information.

In a specific application, for the recurring trajectory after speed planning is completed, the speed is substituted into the posture curve of the recurring trajectory to obtain position information for each interpolation cycle. Then control the robot to move according to the position information to realize the reproduction of the teaching trajectory of the robot.

The method for reproducing the teaching trajectory of the industrial robot provided by this embodiment collects the joint information of the robot, obtains the posture information based on the information of each joint and filters it, and performs continuous repetition based on the filtered posture information. The trajectory is reduced, the error of the end position and pose is reduced, and the curvature of the trajectory is continuous. The speed of the generated trajectory is planned to ensure that the speed of the trajectory is controlled. The method of teaching trajectory reproduction has the problems of large end pose error, uncontrollable change of pose velocity and discontinuous pose curve.

Example two:

As shown in FIG. 3, in this embodiment, step S101 in Embodiment 1 specifically includes:

Step S201: Drag the robot to generate a teaching trajectory, and collect the joint information of the robot.

In specific applications, by dragging the robot, the robot generates a teaching trajectory and collects joint information of each joint of the robot. Information about each joint of the robot can be collected by sensors at each joint of the robot. It is also possible to collect information about each joint of the robot through an encoder installed at the robot joint or motor end, which is not limited.

Step S202: Determine the Cartesian pose information of the end pose of the robot based on the forward kinematics of the robot according to the joint information of the robot.

It should be noted that the method for determining the Cartesian pose information of the end pose of the robot based on the forward kinematics of the robot based on the joint information of the robot is used as a prior art method, and the existing determination method can be used to Implementation, will not repeat them here.

Step S203: Filter the acquired Cartesian pose information to eliminate the noise of the pose information.

In specific applications, the joint position value is filtered to eliminate high-frequency jitter. Specifically, by analyzing the actual experimental data, it can be found that when dragging at a low speed or a high speed, there is a certain high frequency jitter in the joint position collected by the sensor, and the noise of the pose information (high frequency jitter) needs to be eliminated by filtering. The filtering can be in the form of a band-rejection filter combined with a band-pass filter. The band-rejection filter filters out jitter at a specific frequency of the hand, and the band-pass filter eliminates high-frequency jitter caused by friction, while retaining the desired trajectory information.

Example three:

As shown in FIG. 4, in this embodiment, step S102 in Embodiment 1 specifically includes:

Step S301: Fit the collected pose information with Nurbs curve to obtain a continuous recurring trajectory; the pose information includes position information and pose information.

In specific applications, for the collected location information

The Nurbs curve is used for fitting to obtain a continuous position curve. The continuous position curve is:

Where d _i is the position curve control vertex, w _i is the weight factor,

B-spline basis function of order p;

In specific applications, for the collected posture information

The Nurbs curve is used for fitting to obtain a continuous posture curve. The continuous posture curve is:

among them,

Is the vertex of the Nurbs curve control, w _i is the weighting factor,

B-spline basis function of order p.

In specific applications, B-spline curve fitting can ensure the curvature continuity of the generated curve.

Example 4:

As shown in FIG. 5, in this embodiment, step S103 in Embodiment 1 specifically includes:

Step S401: Calculate the total length of the position curve according to the recurring trajectory.

In a specific application, the calculation formula for calculating the total length of the position curve according to the recurring trajectory is:

Among them, P′(u) is the first derivative of P(u) to the parameter u, and P(u) is the position curve of the recurring trajectory. It should be noted that the approximate solution of the total length of the position curve can be obtained by the numerical integration method.

Step S402: Calculate the running speed of the recurring trajectory according to the collection time and the total length of the position curve.

In specific applications, the calculation formula for calculating the running speed of the recurring trajectory according to the acquisition time and the total length of the position curve is

Among them, T _t is the acquisition time.

Example 5:

As shown in FIG. 6, this embodiment provides a teaching trajectory reproduction system 100 for an industrial robot, which is used to execute the method steps in Embodiment 1, which includes a pose information acquisition module 101, a fitting module 102, and a speed calculation Module 103, speed planning module 104 and motion control module 105.

The posture information obtaining module 101 is used to collect the joint information of the robot, obtain the posture information of the terminal posture according to the joint information of the robot, and filter the posture information.

The fitting module 102 is used to fit the posture information after filtering to obtain a continuous recurring trajectory.

The speed calculation module 103 is used to calculate the running speed of the recurring trajectory according to the recurring trajectory.

The speed planning module 104 is used for speed planning of the recurring trajectory according to the moving speed of the recurring trajectory.

The motion control module 105 is used to obtain the position information of each interpolation cycle of the recurring trajectory according to the speed planning result, and control the robot to move according to the position information.

It should be noted that the teaching trajectory reproduction system of the industrial robot provided by the embodiment of the present invention is based on the same concept as the method embodiment shown in FIG. 1 of the present invention, and the technical effect brought by it is the same as the method shown in FIG. 1 of the present invention. The embodiments are the same, and the specific content can refer to the description in the method embodiment shown in FIG. 1 of the present invention, which is not repeated here.

Therefore, the teaching trajectory reproduction system of an industrial robot provided by this embodiment can also collect the joint information of the robot, and obtain and filter the pose information based on the information of each joint, and make a simulation based on the filtered pose information The combined continuous recurring trajectories reduce the end position and pose errors while ensuring the curvature of the recurring trajectories is continuous, and the speed planning of the generated recurring trajectories is carried out to ensure that the speed of the trajectory recurring process is controllable and effectively solved The current method of dragging teaching trajectory reproduction has the problems of large end pose error, uncontrollable change of pose velocity and discontinuous pose curve.

Example 6:

As shown in FIG. 7, in this embodiment, the pose information acquisition module 101 in Embodiment 5 includes a structure for executing the method steps in the embodiment corresponding to FIG. 3, which includes an acquisition unit 201 and a determination unit 202与filterunit 203.

The collection unit 201 is used to drag the robot to generate a teaching trajectory, and collect the joint information of the robot.

The determining unit 202 is configured to determine the Cartesian pose information of the end pose of the robot based on the forward kinematics of the robot according to the joint information of the robot.

The filtering unit 203 is used to filter the acquired Cartesian pose information to eliminate the noise of the pose information.

Example 7:

As shown in FIG. 8, in this embodiment, the fitting module 102 in the fifth embodiment includes a structure for executing the method steps in the embodiment corresponding to FIG. 4, which includes a fitting unit 301.

The fitting unit 301 is used to fit the collected pose information using Nurbs curve to obtain a continuous recurring trajectory; the pose information includes position information and pose information.

For collected location information

Where d _i is the position curve control vertex, w _i is the weight factor,

B-spline basis function of order p;

For the collected posture information

among them,

Is the vertex of the Nurbs curve control, w _i is the weighting factor,

B-spline basis function of order p.

Example 8:

As shown in FIG. 9, in this embodiment, the speed calculation module 103 in Embodiment 5 includes a structure for executing the method steps in the embodiment corresponding to FIG. 5, which includes a first calculation unit 401 and a second calculation Unit 402.

The first calculation unit 401 is used to calculate the total length of the position curve according to the recurring trajectory.

The second calculation unit 402 is used to calculate the running speed of the recurring trajectory according to the acquisition time and the total length of the position curve.

Example 9:

FIG. 10 is a schematic diagram of a robot provided in Embodiment 7 of the present invention. As shown in FIG. 10, the robot 9 of this embodiment includes a processor 90, a memory 91, and a computer program 92 stored in the memory 91 and executable on the processor 90, for example, a program. When the processor 90 executes the computer program 92, the steps in the above embodiments of each picture processing method are implemented, for example, steps S101 to S105 shown in FIG. 1. Alternatively, when the processor 90 executes the computer program 92, the functions of each module/unit in the above-described system embodiment are realized, for example, the functions of the modules 101 to 105 shown in FIG. 6.

Exemplarily, the computer program 92 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 91 and executed by the processor 90 to complete this invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 92 in the robot 9. For example, the computer program 92 may be divided into a pose information acquisition module, a fitting module, a speed calculation module, a speed planning module, and a motion control module. The specific functions of each module are as follows:

The so-called processor 90 can be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 91 may be an internal storage unit of the robot 9, such as a hard disk or a memory of the robot 9. The memory 91 may also be an external storage device of the robot 9, such as a plug-in hard disk equipped on the robot 9, a smart memory card (Smart) Media (SMC), and a secure digital (SD) card. Flash card (Flash Card), etc. Further, the memory 91 may also include both an internal storage unit of the robot 9 and an external storage device. The memory 91 is used to store the computer program and other programs and data required by the robot. The memory 91 can also be used to temporarily store data that has been or will be output.

Those skilled in the art can clearly understand that, for convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example for illustration. In practical applications, the above-mentioned functions can be allocated by different functional units, Module completion means that the internal structure of the system is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above integrated unit may use hardware It can also be implemented in the form of software functional units. In addition, the specific names of each functional unit and module are only for the purpose of distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working processes of the above units and modules in the wireless terminal, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the above embodiments, the description of each embodiment has its own emphasis. For a part that is not detailed or recorded in an embodiment, you can refer to the related descriptions of other embodiments.

Those of ordinary skill in the art may realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application of the technical solution and design constraints. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

In the embodiments provided by the present invention, it should be understood that the disclosed system/robot and method may be implemented in other ways. For example, the system/robot embodiments described above are only schematic. For example, the division of the module or unit is only a logical function division. In actual implementation, there may be other division modes, such as multiple units or Components can be combined or integrated into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, systems or units, and may be in electrical, mechanical or other forms.

The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or may be distributed to multiple network units on. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or software function unit.

If the integrated module/unit is implemented in the form of a software functional unit and set as an independent product for sale or use, it may be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, and can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the program is executed by the processor, the steps of the foregoing method embodiments may be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file, or some intermediate form, etc. The computer-readable medium may include any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, and a read-only memory (ROM). , Random Access Memory (RAM, Random Access Memory), electrical carrier signals, telecommunications signals and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in jurisdictions. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media Excluded are electrical carrier signals and telecommunications signals. The above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, persons of ordinary skill in the art should understand that they can still implement the foregoing The technical solutions described in the examples are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not deviate from the essence and scope of the technical solutions of the embodiments of the present invention, and should be included in Within the protection scope of the present invention.

Claims

A method for reproducing the teaching trajectory of an industrial robot, which is characterized by:

Collect the joint information of the robot, obtain the posture information of the terminal posture according to the joint information of the robot, and filter the posture information;

Fit the posture information after filtering to obtain continuous recurring trajectories;

Calculating the running speed of the recurring trajectory according to the recurring trajectory;

Performing speed planning on the recurring trajectory according to the moving speed of the recurring trajectory;

The position information of each interpolation cycle of the recurring trajectory is obtained according to the speed planning result, and the robot is controlled to move according to the position information.
The method according to claim 1, wherein the collecting the joint information of the robot, acquiring the posture information of the terminal posture according to the joint information of the robot, and filtering the posture information includes: :

Drag the robot to produce a teaching trajectory and collect the joint information of the robot;

Determining the Cartesian pose information of the end position of the robot based on the forward kinematics of the robot according to the joint information of the robot;

Filter the obtained Cartesian pose information to eliminate the noise of pose information.
The method according to claim 1, wherein the fitting of the filtered pose information to obtain a continuous recurring trajectory includes:

Fit the collected pose information with Nurbs curve to obtain a continuous recurring trajectory; the pose information includes position information and pose information;

For collected location information
The Nurbs curve is used for fitting to obtain a continuous position curve. The continuous position curve is:
Where d i is the position curve control vertex, w i is the weight factor,
B-spline basis function of order p;

For the collected posture information
The Nurbs curve is used for fitting to obtain a continuous posture curve. The continuous posture curve is:
among them,
Is the vertex of the Nurbs curve control, w i is the weighting factor,
B-spline basis function of order p.
The method according to claim 1, wherein the calculating the running speed of the recurring trajectory according to the recurring trajectory includes:

Calculate the total length of the position curve according to the recurring trajectory;

According to the acquisition time and the total length of the position curve, the running speed of the recurring trajectory is calculated.
The method according to claim 4, characterized in that:

The formula for calculating the total length of the position curve according to the recurring trajectory is:
Where P′(u) is the first derivative of P(u) to the parameter u, and P(u) is the position curve of the recurring trajectory;

The calculation formula for calculating the running speed of the recurring trajectory according to the acquisition time and the total length of the position curve is:
Among them, T t is the acquisition time.
A teaching trajectory reproduction system for industrial robots, characterized by including:

The posture information acquisition module is used to collect the joint information of the robot, obtain the posture information of the terminal posture according to the joint information of the robot, and filter the posture information;

The fitting module is used to fit the posture information after filtering to obtain a continuous recurring trajectory;

A speed calculation module, used to calculate the running speed of the recurring trajectory according to the recurring trajectory;

A speed planning module, configured to perform speed planning on the recurring trajectory according to the moving speed of the recurring trajectory;

The motion control module is used to obtain the position information of each interpolation cycle of the recurring trajectory according to the speed planning result, and control the robot to move according to the position information.
The teaching track reproduction system according to claim 6, wherein the posture information acquisition module includes:

The collection unit is used for dragging the robot to generate a teaching trajectory and collecting the joint information of the robot;

A determining unit, configured to determine the Cartesian pose information of the end position of the robot based on the forward kinematics of the robot based on the joint information of the robot;

The filtering unit is used to filter the acquired Cartesian pose information and eliminate the noise of the pose information.
The teaching trajectory reproduction system according to claim 6, wherein the speed calculation module comprises:

A first calculation unit, configured to calculate the total length of the position curve according to the recurring trajectory;

The second calculation unit is used to calculate the running speed of the recurring trajectory according to the acquisition time and the total length of the position curve.
A robot, including a memory, a processor, and a computer program stored in the memory and runable on the processor, characterized in that, when the processor executes the computer program, claims 1 to 6 are implemented Any one of the steps of the method.
A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.