A control method, device, and system for an industrial robot

Abstract

The application relates to a control method, device and system of an industrial robot. The control method of the industrial robot comprises the following steps: preprocessing the dragging speed data of a magnetic dragging demonstrator which is dragged in the vicinity of a tool center point of an industrial robot, obtaining a dragging posture coordinate set; aligning the dragging posture coordinate set and a dragging torque set with time stamps, obtaining a demonstration data set; performing coordinate system conversion on the demonstration data set according to calibration data, obtaining the dragging posture coordinate set and the dragging torque set of the current tool center point, and performing interpolation and tool point allocation, thereby completing the definition of the task path of the corresponding tool center point of the industrial robot. The control method of the industrial robot greatly improves the accuracy of the TCP task path; meanwhile, the control method effectively supports the task planning of multiple TCPs, and significantly improves the flexibility and task execution accuracy of the industrial robot control method.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent teaching of industrial robots, and in particular to a control method and device of an industrial robot, a control system, an electronic device and a computer storage medium. BACKGROUND

[0002] In the field of industrial robots, a teach pendant is an important tool for teaching and debugging the motion of a robot. Through the teach pendant, an engineer can manually control the position of the end effector or tool of the robot, and define the motion trajectory and task path of the robot or robotic arm. However, in the traditional teach pendant, the engineer needs to remotely control or manually operate the teach pendant, and make it record the key path points or specific poses of the robot or robotic arm, so that the subsequent robot can operate automatically according to the key path points or positions. However, through remote control or manual operation, the engineer needs to have certain experience and skills to improve the precision and accuracy of the robot or robotic arm during operation, otherwise it is easy to cause operation errors of the robot or robotic arm.

[0003] Therefore, the existing technology adopts a drag teach pendant connected with the robot or robotic arm, so as to allow the engineer to directly drag the drag teach pendant and drive the end effector or tool of the robot or robotic arm, so as to obtain the motion trajectory or path key points of the robot or robotic arm driven thereby, thereby reducing the complexity of operation and significantly improving the flexibility and accuracy of the teaching process.

[0004] However, the existing teach pendant is generally rigidly connected, so that during the setting of a complex task, the motion of multiple joints or tools is easy to produce coupling effect, thereby affecting the movement trajectory of the robot or robotic arm during automatic execution of the task. Therefore, during the use of the drag teach pendant, it is also necessary to additionally debug the coupling force and the center of mass moment, so as to ensure high-precision calculation and avoid instability or control errors. At the same time, since there is a certain distance between the Tool Central Point (TCP) of the robot end effector or tool and the rigidly connected drag teach pendant, directly using the spatial position of the drag teach pendant as the movement trajectory is easy to produce a certain deviation, and it is often necessary to finely calibrate to ensure that the movement trajectory is highly overlapped with the movement trajectory of the tool central point. In addition, when the industrial robot is provided with multiple tools, i.e. multiple tools are installed on a flange, the cost of installing a moment sensor at the end of each tool for drag teaching is high. Accordingly, the control method of the industrial robot of the existing technology has the problems of high control cost, low flexibility and low TCP accuracy. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a control method of an industrial robot.

[0006] A control method of an industrial robot, comprising the following steps:

[0007] S1: Preprocessing the dragging speed data of a magnetic attraction dragging demonstrator to obtain a set of dragging pose coordinates; wherein the magnetic attraction dragging demonstrator is adsorbed in the adjacent area of the tool center point of an industrial robot, and is used to measure the set of dragging speed data and dragging torque generated in three-dimensional space when the industrial robot is dragged by the magnetic attraction dragging demonstrator; the dragging speed data includes linear acceleration and angular velocity; the set of dragging torque includes torque and linear force;

[0008] S2: Time stamp alignment of the set of dragging pose coordinates and the set of dragging torque to obtain a set of teaching data;

[0009] S3: Coordinate system conversion of the set of teaching data according to the calibration data to obtain the set of dragging pose coordinates and the set of dragging torque of the current tool center point;

[0010] S4: Interpolation of the set of dragging pose coordinates and the set of dragging torque of the current tool center point to obtain the key point set corresponding to the current tool center point;

[0011] S5: Tool point allocation of the key point set corresponding to the current tool center point to complete the task path definition of the tool center point of the industrial robot.

[0012] The control method of the industrial robot disclosed in the application, compared with the prior art, through the adsorption of the magnetic attraction dragging demonstrator in the TCP adjacent area, and the combination of the calibration data to complete the coordinate system conversion, the low deviation of the tool movement trajectory is realized, and the accuracy of the TCP is significantly improved. At the same time, through the direct collection of the posture and torque data by the external magnetic attraction dragging demonstrator, the need for force coupling and mass center torque debugging in the traditional method is avoided, the teaching operation is effectively simplified, and the operation efficiency of the teaching is improved. In addition, through tool point allocation, the magnetic attraction dragging demonstrator is sequentially adsorbed in multiple TCP adjacent areas to complete the task path definition of the TCP one by one, the flexibility of the teaching process is significantly improved, and the repeatedly used magnetic attraction dragging demonstrator is realized, and the hardware deployment cost is significantly reduced.

[0013] Further, the set of dragging pose coordinates is specifically represented as follows:

[0014] P D ={(p x (t),p y (t),p z (t)),(θ x (t),θ y (t),θ z (t))|t∈[0,N]}

[0015] wherein P D represents the set of drag gesture coordinates; p x (t), p y (t), p z (t) respectively represent the position coordinates of the magnetic drag teach pendant in x, y, z directions at time t, which are specifically obtained by numerically integrating the linear acceleration in three-dimensional space, and the specific calculation is represented as follows:

[0016] p x (t) = ∫a x (t)dt + p x (0)

[0017] p y (t) = ∫a y (t)dt + p y (0)

[0018] p z (t) = ∫a z (t)dt + p z (0)

[0019] wherein a x (t), a y (t), a z (t) represent the linear acceleration of the magnetic drag teach pendant in x, y, z axes at time t; p x (0), p y (0), p z (0) are the initial position coordinates of the teach pendant; θ x (t), θ y (t), θ z (t) respectively represent the rotation angles of the magnetic drag teach pendant in x, y, z axes at time t, which are specifically obtained by numerically integrating the angular velocity in three-dimensional space, and the specific calculation is represented as follows:

[0020] θ x (t) = ∫w x (t)dt + θ x (0)

[0021] θ y (t) = ∫w y (t)dt + θ y (0)

[0022] θ z (t) = ∫w z (t)dt + θ z (0)

[0023] wherein w x (t), w y (t), wz (t) represents the angular velocity data in three-dimensional space measured at time t; θ x (t), θ y (t), θ z (t) is the initial rotation angle of the teach pendant; t is a time stamp, and N represents the longest time for which the user drags the magnetic drag teach pendant.

[0024] The present application converts the linear acceleration and angular velocity of the magnetic drag teach pendant into attitude data in three-dimensional space by numerical integration, to ensure that the teaching data can completely describe the actual motion trajectory of the magnetic drag teach pendant, and divides based on the time stamp to ensure that the attitude data is consistent with the time sequence of the dragging process.

[0025] Further, the step S3 comprises the following sub-steps:

[0026] S31: According to the translation matrix and rotation matrix in the calibration data, coordinate system conversion is performed on the drag attitude coordinate set in the teaching data set to obtain the drag attitude coordinate set of the current tool center point, and is specifically expressed as follows:

[0027] P TCP = {(R TCP ·p xyz (t) + T TCP ), (R TCP θ xyz (t)) | t ∈ [0, N]}

[0028] In the formula, P TCP represents the drag attitude coordinate set of the current tool point, i.e., TCP; R TCP ·p xyz (t) + T TCP represents the result after position coordinate conversion, T TCP is the translation matrix; R TCP is the rotation matrix; p xyz (t) is the drag attitude coordinate under the magnetic drag teach pendant coordinate system at the t-th moment, which contains three components (p x (t), p y (t), p z (t)); θ xyz (t) is the rotation angle under the magnetic drag teach pendant coordinate system at the t-th moment, which contains three components (θ x (t), θ y (t), θ z (t));

[0029] S32: According to the rotation matrix in the calibration data, coordinate system conversion is performed on the drag torque set in the teaching data set to obtain the drag attitude coordinate set of the current tool center point, and is specifically expressed as follows:

[0030] M TCP = {(R TCP ·f xyz (t)),(R TCP ·τ xyz (t))|t∈[0,N]}

[0031] In the formula, M TCP represents the current tool center point drag torque set; f xyz (t) is the force vector set of the t time magnetic attraction drag teach-in device coordinate system, indicating the linear force in the x, y, z direction; τ xyz (t) is the torque vector set of the t time magnetic attraction drag teach-in device coordinate system, indicating the torque data in the x, y, z direction.

[0032] Accordingly, through the translation matrix and the rotation matrix, the drag posture and the torque data of the magnetic attraction drag teach-in device are accurately mapped to the corresponding tool center point in the industrial robot coordinate system, so as to ensure that the pose of the tool center point and the torque data can be accurately matched with the actual operation requirements of the industrial robot, thereby improving the accuracy and dynamic stability of task execution. In addition, the present application directly uses the calibrated TCP position in the industrial robot coordinate system as the reference position of the magnetic attraction drag teach-in device by attracting the magnetic attraction drag teach-in device to the adjacent area of the TCP, which greatly improves the accuracy of the TCP movement path in the path planning process of the industrial robot. At the same time, the error accumulation in the coordinate conversion is reduced, the path deviation problem is effectively avoided, and the accuracy of path generation and the reliability of task execution are significantly improved.

[0033] Further, the step S4 comprises the following sub-steps:

[0034] S41: using spline interpolation to interpolate the drag posture coordinate set of the current center point to obtain a smooth drag posture coordinate set;

[0035] S42: according to the smooth drag posture coordinate set, using spline interpolation to interpolate the drag torque set, and using a low-pass filter to smooth the interpolated drag torque set to obtain a smooth drag torque set;

[0036] S43: time-correlating the smooth drag posture coordinate set and the drag torque set to generate a key point set corresponding to the current tool center point.

[0037] Accordingly, by smoothing the drag posture and drag torque set, the generated key point set can effectively eliminate fluctuations caused by external interference or data acquisition errors, thereby ensuring the continuity and smoothness of the data. Therefore, the smoothed key point set can be used by the industrial robot to plan a path according to its own dynamic constraints, to generate a more stable TCP movement path, thereby improving the stability and accuracy of the task execution process.

[0038] A control device of an industrial robot, comprising a drag speed data preprocessing unit, a data timestamp alignment unit, a coordinate system conversion unit, a path planning unit and a tool point path allocation unit.

[0039] The drag speed data preprocessing unit is configured to preprocess the drag speed data of a magnetic attraction drag teach pendant to obtain a drag posture coordinate set. The magnetic attraction drag teach pendant is attracted to the vicinity of the tool center point of an industrial robot, and is used to measure the drag speed data and drag torque set generated in three-dimensional space when the industrial robot is dragged by the magnetic attraction drag teach pendant. The drag speed data includes linear acceleration and angular velocity. The drag torque set includes torque and linear force.

[0040] The data timestamp alignment unit is configured to align the timestamps of the drag posture coordinate set and the drag torque set to obtain a teaching data set.

[0041] The coordinate system conversion unit is configured to convert the coordinate system of the teaching data set according to calibration data to obtain a drag posture coordinate set and a drag torque set of the current tool center point.

[0042] The path planning unit is configured to interpolate the drag posture coordinate set and the drag torque set of the current tool center point to obtain a key point set corresponding to the current tool center point.

[0043] The tool point path allocation unit is configured to allocate tool points to the key point set corresponding to the current tool center point to complete the definition of the task path of the corresponding tool center point of the industrial robot.

[0044] Further, the drag posture coordinate set is specifically represented as follows:

[0045] P D = {(p x (t), p y (t), p z (t)), (θ x (t), θ y (t), θ z (t)) | t ∈ [0, N]}

[0046] In the formula, PD represents the set of coordinates of the dragging posture; p x (t), p y (t), p z (t) respectively represent the position coordinates of the magnetic drag teach pendant in x, y, z directions at time t, which are specifically obtained by numerically integrating the linear acceleration in three-dimensional space, and the specific calculation is represented as follows:

[0047] p x (t) = ∫a x (t)dt + p x (0)

[0048] p y (t) = ∫a y (t)dt + p y (0)

[0049] p z (t) = ∫a z (t)dt + p z (0)

[0050] wherein a x (t), a y (t), a z (t) represent the linear acceleration of the magnetic drag teach pendant in x, y, z axes at time t; p x (0), p y (0), p z (0) are the initial position coordinates of the teach pendant; θ x (t), θ y (t), θ z (t) respectively represent the rotation angles of the magnetic drag teach pendant in x, y, z axes at time t, which are specifically obtained by numerically integrating the angular velocity in three-dimensional space, and the specific calculation is represented as follows:

[0051] θ x (t) = ∫w x (t)dt + θ x (0)

[0052] θ y (t) = ∫w y (t)dt + θ y (0)

[0053] θ z (t) = ∫w z (t)dt + θ z (0)

[0054] wherein w x (t), w y (t), w z(t) represents the angular velocity data in three-dimensional space measured at time t; θ x (t), θ y (t), θ z (t) is the initial rotation angle of the teaching pointer; t is a time stamp, and N represents the longest time for which the user drags the magnetic drag teaching pointer.

[0055] Further, the coordinate system conversion unit is further configured to perform the following sub-steps:

[0056] According to the translation matrix and the rotation matrix in the calibration data, the drag posture coordinate set in the teaching data set is converted in the coordinate system, and a drag posture coordinate set of the current tool center point is obtained, and is specifically represented as follows:

[0057] P TCP = {(R TCP · p xyz (t) + T TCP ), (R TCP θ xyz (t)) | t ∈ [0, N]}

[0058] In the formula, P TCP represents the drag posture coordinate set of the current tool point, i.e., TCP; R TCP · p xyz (t) + T TCP represents the result after position coordinate conversion, T TCP is the translation matrix; R TCP is the rotation matrix; p xyz (t) is the drag posture coordinate in the magnetic drag teaching pointer coordinate system at the t-th moment, including three components (p x (t), p y (t), p z (t)); θ xyz (t) is the rotation angle in the magnetic drag teaching pointer coordinate system at the t-th moment, including three components (θ x (t), θ y (t), θ z (t));

[0059] S32: According to the rotation matrix in the calibration data, the drag torque set in the teaching data set is converted in the coordinate system, and a drag posture coordinate set of the current tool center point is obtained, and is specifically represented as follows:

[0060] M TCP = {(R TCP · f xyz (t)), (R TCP · τ xyz (t)) | t ∈ [0, N]}

[0061] M TCP a set of drag torques representing the current tool center point; f xyz (t) is a set of force vectors in the magnetic drag teach pendant coordinate system at the t time, representing linear forces in the x, y, z directions; τ xyz (t) is a set of torque vectors in the magnetic drag teach pendant coordinate system at the t time, representing torque data in the x, y, z directions.

[0062] A control system of an industrial robot, comprising a magnetic drag teach pendant and a control device; the magnetic drag teach pendant is fixed by magnetic adsorption in the vicinity of a tool center point of an industrial robot, and is in communication connection with the control device, for measuring the attitude speed change and torque change of the magnetic drag teach pendant in three-dimensional space, so as to obtain a set of drag speed data and drag torques, and input to the control device;

[0063] The magnetic drag teach pendant comprises a drag handle, a six-dimensional force sensor and an electromagnet which are fixedly connected in sequence.

[0064] The drag handle is used for dragging the tool center point of the industrial robot to displace under external force.

[0065] The six-dimensional force sensor is used for measuring linear forces and torques generated in three-dimensional space, and converting them into electrical signals to form a set of drag torques, and inputting them to the control device.

[0066] The six-axis sensor comprises three accelerometers and three gyroscopes, and is used for measuring linear acceleration and angular velocity in three-dimensional space, and inputting them as drag speed data to the control device.

[0067] The electromagnet generates a magnetic force through electrical connection, and is used for being fixed by magnetic adsorption in the vicinity of the tool center point of the industrial robot.

[0068] The control device is the control device of the industrial robot.

[0069] In order to better understand and implement, the present application is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 A simple installation schematic diagram for installing the magnetic drag teach pendant to the industrial robot;

[0071] Figure 2 A simple structure schematic diagram of the magnetic drag teach pendant;

[0072] Figure 3 A simple structure schematic diagram of the magnetic drag teach pendant disassembled;

[0073] Figure 4 A simple structure diagram of a control device of an industrial robot according to the present application;

[0074] Figure 5 A simple flow diagram of a control method of an industrial robot according to the present application. DETAILED DESCRIPTION

[0075] In order to solve the problems of high control cost, low flexibility and low TCP accuracy in the prior art, the present application obtains the dragging speed data of the magnetic drag demonstrator to solve the dragging pose coordinates, timestamps the dragging pose coordinates and the corresponding torque set, and obtains the registered dragging pose coordinates and the corresponding torque set; then, the registered dragging pose coordinates are converted in the coordinate system, and the converted dragging pose coordinates and the corresponding dragging torque combination are combined to plan the path and obtain the movement trajectory corresponding to the current tool center point; finally, the tool point is distributed according to the trajectory, and the task path definition of the current tool center point is completed. Accordingly, the present application greatly improves the accuracy of the TCP task path by customizing the installation position of the magnetic drag demonstrator, reduces the use of torque sensors, and effectively reduces the teaching cost; at the same time, the data of a single magnetic drag demonstrator is processed to generate a key point set corresponding to multiple tool center points of the industrial robot, thereby effectively supporting the task planning of multiple TCPs, and significantly improving the flexibility and task execution accuracy of the industrial robot control method.

[0076] Based on the above design, the present application proposes a control method of an industrial robot, and based on the method, a control system of an industrial robot is proposed.

[0077] Please refer to Figure 1 , Figure 1 A simple installation diagram of the magnetic drag demonstrator installed on the industrial robot.

[0078] The control system of the industrial robot includes an industrial robot 101, a magnetic drag demonstrator 102 and a control device 103 of the industrial robot. The industrial robot 101 is in communication connection with the control device 103 of the industrial robot, for receiving the task path instruction of the control device, and adjusting the movement trajectory of the end effector of the industrial robot according to the task path instruction.

[0079] Among them, the industrial robot 101 is provided with multiple end effectors, and the end effectors are used to install various working tools, and the center coordinates of the corresponding tools are tool center points (TCP), and the TCP is used to define the coordinate point of the tool installation position and direction, and by adjusting different TCPs, the robot can more flexibly perform various tasks.

[0080] Meanwhile, the industrial robot can include multiple joints, and the joints can adopt linear joints, rotary joints, and spherical joints, and precise positioning and multi-degree-of-freedom motion of the end effector are achieved by cooperating these joints; however, the types, numbers, or axes of the joints adopted by different industrial robots can be different, and therefore, when performing path planning, the coupling effects of these joints in the motion process need to be considered. Therefore, the industrial robot usually needs to perform path planning on the path key point set input by the control device in combination with its own dynamic constraints, including joint speed, acceleration, load, etc., and an optimization algorithm is adopted to ensure that each axis can move coordinately, so that the TCP runs smoothly along the predetermined trajectory.

[0081] It should be noted that, since each TCP corresponds to a different tool mounting position, different tools can be selected for mounting according to task requirements, so as to achieve fine operation on different tasks, such as welding, grabbing, or assembly, etc., and therefore, the type of tool mounted by the TCP is not specifically limited herein.

[0082] The magnetic drag demonstrator 102 is magnetically attracted and fixed to the TCP adjacent area of the industrial robot 101, and is in communication connection with the control device 103 of the industrial robot, for measuring the attitude speed change and torque change of the magnetic drag demonstrator in the three-dimensional space, so as to obtain a drag speed data set and a drag torque set, and input them to the control device 103 of the industrial robot.

[0083] The magnetic drag demonstrator 102 includes a drag handle 1021, a six-dimensional force sensor 1022, a six-axis sensor 1023, and an electromagnet 1024 which are fixedly connected in sequence, and specific reference can be made to Figure 2 and Figure 3 , Figure 2 for the simple structure diagram of the magnetic drag demonstrator, Figure 3 for the simple structure diagram of the magnetic drag demonstrator disassembled,

[0084] The drag handle 1021 is used for manual dragging by the user to pull the TCP of the industrial robot to displace;

[0085] The six-dimensional force sensor 1022 is used for measuring the linear force (size and direction of force) and torque generated in the three-dimensional space, converting them into electrical signals, forming a drag torque set, and inputting them to the control device;

[0086] The six-axis sensor 1023 includes three accelerometers and three gyroscopes, and is used for measuring the linear acceleration and angular velocity in the three-dimensional space, and inputting them as drag speed data to the control device;

[0087] The electromagnet 1024 generates magnetic force through electrical connection, and is used for being adsorbed in the TCP adjacent area of the industrial robot 101 through magnetic force, so as to ensure that the magnetic drag teaching device 102 stably drags the TCP displacement of the industrial robot during the teaching process.

[0088] Please refer to Figure 4 and Figure 5 , Figure 4 for the simple structure diagram of the control device of the industrial robot, Figure 5 for the simple flow diagram of the control method of the industrial robot.

[0089] The control device 103 of the industrial robot includes a drag speed data preprocessing unit 1, a data timestamp alignment unit 2, a coordinate system conversion unit 3, a path planning unit 4 and a tool point path distribution unit 5.

[0090] The drag speed data preprocessing unit 1 is used to perform step S1: pre-processing according to the drag speed data of the magnetic drag teaching device, to obtain a drag posture coordinate set.

[0091] Specifically, the drag posture coordinate set is obtained by calculating three-dimensional linear acceleration and three-dimensional angular velocity, and the drag posture coordinate set is specifically represented as follows:

[0092] P D ={(p x (t),p y (t),p z (t)),(θ x (t),θ y (t),θ z (t))|t∈[0,N]}

[0093] In the formula, P D represents the drag posture coordinate set; p x (t), p y (t), and p z (t) respectively represent the position coordinates of the magnetic drag teaching device in the x, y, and z directions at time t, and the specific calculation is represented as follows:

[0094] By numerically integrating the linear acceleration in three-dimensional space, the position coordinates are obtained, and the numerical integration calculation is represented as follows:

[0095] p x (t)=∫a x (t)dt+p x (0)

[0096] p y (t)=∫a y (t)dt+py (0)

[0097] p z (t)=∫a z (t)dt+p z (0)

[0098] wherein a x (t), a y (t), a z (t) represents the linear acceleration of the magnetic drag teaching pendant in the x, y, z axis at time t; p x (0), p y (0), p z (0) is the initial position coordinate of the teaching pendant; θ x (t), θ y (t), θ z (t) are the rotation angles of the magnetic drag teaching pendant in the x, y, z axis at time t, i.e. the attitude angles, which are specifically calculated and obtained as follows:

[0099] The rotation angles of the corresponding axis are obtained by numerical integration calculation of the angular velocity in the three-dimensional space, and the numerical integration calculation is represented as follows:

[0100] θ x (t)=∫w x (t)dt+θ x (0)

[0101] θ y (t)=∫w y (t)dt+θ y (0)

[0102] θ z (t)=∫w z (t)dt+θ z (0)

[0103] wherein w x (t), w y (t), w z (t) represents the angular velocity data in the three-dimensional space measured at time t; θ x (t), θ y (t), θ z (t) is the initial rotation angle of the teaching pendant, i.e. the initial attitude angle, which is usually given when the teaching pendant is started; t is a time stamp, which is used to represent the collection time of each data point corresponding to the drag attitude, and N represents the longest time of the user dragging the magnetic drag teaching pendant.

[0104] Accordingly, the position and posture of the magnetic attraction drag demonstrator in the three-dimensional space are accurately obtained by converting the linear angular velocity and angular velocity into the posture, so as to provide the posture information corresponding to the high-precision motion trajectory for subsequent path planning and industrial robots.

[0105] The data timestamp alignment unit 2 is configured to perform step S2: timestamp alignment on the drag pose coordinate set and the drag torque set, to obtain a teaching data set.

[0106] Specifically, the teaching data set D T is specifically represented as follows:

[0107] D T =(P D ,M D )=(P D ,((f x (t),f y (t),f z (t)),(τ x (t),τ y (t),τ z (t)))|t∈[0,N]}

[0108] In the formula, P D represents the drag pose coordinate set; M D represents the drag torque set; (P D , M D ) represents the registered drag pose coordinate set and drag torque set; f x (t), f y (t), and f z (t) respectively represent the linear force in the x, y, and z directions at time t, and the three-dimensional force data is collected in real time by the six-dimensional force sensor, for reflecting the external force change of the magnetic attraction drag demonstrator in the three directions; τ x (t), τ y (t), and τ z (t) respectively represent the torque in the x, y, and z directions at time t, i.e., the torque data obtained by the six-dimensional force sensor.

[0109] Accordingly, the one-to-one correspondence relationship between the pose and torque data obtained at the same time t is ensured by aligning the timestamps t of the drag pose coordinate set and the drag torque set, so as to ensure the synchronization of the physical state corresponding to each pair of drag pose and drag torque.

[0110] The coordinate system conversion unit 3 is configured to perform step S3: coordinate system conversion on the teaching data set according to the calibration data, to obtain the drag pose coordinate set and the drag torque set of the current tool center point.

[0111] Specifically, according to the translation matrix and the rotation matrix in the calibration data, the coordinate system conversion is performed on the drag posture coordinate set in the teaching data set, and a drag posture coordinate set of the current tool center point is obtained, and the specific expression is as follows:

[0112] P TCP = {(R TCP ·p xyz (t)+T TCP ), (R TCP θ xyz (t)) | t ∈ [0, N]}

[0113] In the formula, P TCP represents a drag posture coordinate set of the current tool point (TCP), which is used to represent the posture data set of the corresponding TCP coordinate as a starting point converted from the magnetic suction drag teach-in coordinator to the geodetic coordinate system;

[0114] R TCP ·p xyz (t)+T TCP represents the result after the position coordinate conversion, and T TCP is a translation matrix, which represents the translation deviation between the geodetic coordinate system and the magnetic suction drag teach-in coordinator, and is used to adjust the position coordinate of the magnetic suction drag teach-in coordinator to the specific coordinate of the TCP in the geodetic coordinate system as a starting point according to the position coordinate of the TCP in the geodetic coordinate system; R TCP is a rotation matrix, which is used to convert the coordinate in the magnetic suction drag teach-in coordinator to the rotation part of the geodetic coordinate system, and is used to describe the rotation relationship between the coordinate systems, so as to ensure that the angles between the magnetic suction drag teach-in coordinator and the geodetic coordinate system are aligned, so that the relative direction between the magnetic suction drag teach-in coordinator and the geodetic coordinate system can be correctly converted;

[0115] The translation matrix and the rotation matrix are obtained through the calibration data of the corresponding TCP of the industrial robot, and the calibration data includes tool center point identification information, translation matrix and rotation matrix corresponding to the tool center point, and task type, which are used to clearly distinguish different tool center points of the industrial robot. Since the definition of the geodetic coordinate system and the tool center point (TCP) of each industrial robot may deviate during design and use, the conversion relationship between the geodetic coordinate system and the magnetic suction drag teach-in coordinator of each industrial robot may also be different. Accordingly, the specific form of the translation matrix and the rotation matrix is not specifically limited, but the calibration data of the corresponding tool center point of the industrial robot is obtained to ensure that the coordinates of the teach-in coordinator can be correctly adjusted to the position of the TCP in the geodetic coordinate system.

[0116] pxyz(t) is the drag posture coordinate of the magnetic suction drag teach-in coordinator at the t time, which includes three components, that is, (p x(t), p y (t), p z (t));

[0117] θ xyz (t) is the rotation angle at the t-th moment in the magnetic suction drag teach pendant coordinate system, which contains three components, namely (θ x (t), θ y (t), θ z (t)).

[0118] Then, according to the rotation matrix in the calibration data, the drag torque set in the teaching data set is converted in the coordinate system, and the drag pose coordinate set of the current tool center point is obtained, which is specifically expressed as follows:

[0119] M TCP = {(R TCP ·f xyz (t), (R TCP ·τ xyz (t)) | t ∈ [0, N]}

[0120] In the formula, M TCP represents the drag torque set of the current tool center point, which is used to represent the force and torque data set corresponding to the TCP position converted from the magnetic suction drag teach pendant coordinate system to the geodetic coordinate system; f xyz (t) is the force vector set in the magnetic suction drag teach pendant coordinate system at the t-th moment, which represents the linear force in the x, y and z directions; τ xyz (t) is the torque vector set in the magnetic suction drag teach pendant coordinate system at the t-th moment, which represents the torque data in the x, y and z directions.

[0121] Wherein, the force and torque vector in the magnetic suction drag teach pendant coordinate system is converted to the geodetic coordinate system of the industrial robot through the rotation matrix, so as to ensure that the industrial robot can accurately understand and process the force and torque data of the current tool center point (TCP) in the geodetic coordinate system, and then realize the coordinate system alignment between the magnetic suction drag teach pendant and the industrial robot, so that the industrial robot can adjust the action according to the correct force feedback, and effectively perform the precise task.

[0122] In addition, since the calibration data may involve multiple tool center points (TCP), the present application selects the TCP closest to the magnetic suction drag teach pendant adsorption position by the user, and automatically matches the corresponding calibration data, so that the data collected by the magnetic suction drag teach pendant can accurately reflect the movement trajectory of the target TCP after coordinate system conversion, thereby realizing the free debugging of multiple tool points and the repeated use effect of multiple robots, and effectively reducing the hardware cost of system deployment.

[0123] The smoothing processing unit 4 is used to perform step S4: interpolating the current tool center point according to the set of drag posture coordinates of the current tool center point and the set of drag moments to obtain the key point set corresponding to the current tool center point.

[0124] Specifically, the set of drag posture coordinates of the current center point is interpolated by using spline interpolation to obtain a set of smooth drag posture coordinates, and the spline interpolation can be cubic spline interpolation, which generates a fourth-order equation for each coordinate direction in the time interval [0, N] through cubic spline interpolation, and solves the equation coefficients by using Gaussian elimination or matrix method, thereby ensuring smooth transition of the path trajectory in the entire time interval, avoiding sudden changes, and further improving the executability and stability of the path.

[0125] Among them, since there are many choices of spline interpolation, B-spline interpolation, Lagrange interpolation, Hermite interpolation, Spline interpolation or linear interpolation can be selected according to different requirements to realize smooth path generation; therefore, the selection of spline interpolation is not specifically limited in the present application, but a suitable interpolation method is selected according to the task requirement.

[0126] Then, according to the set of smooth drag posture coordinates, the set of drag moments is interpolated by using spline interpolation, and the set of interpolated drag moments is smoothed by using a low-pass filter to obtain a set of smooth drag moments.

[0127] Among them, the spline interpolation uses the same interpolation method as the set of smooth drag posture coordinates to ensure the alignment between the moment data and the drag posture data, thereby maintaining consistent smooth transition. The low-pass filter is used to filter and smooth the set of interpolated drag moments, thereby ensuring smooth changes of linear force and moment data, avoiding large fluctuations, and further improving the stability and accuracy of the robot when performing tasks.

[0128] Finally, the set of smooth drag posture coordinates and the set of drag moments are time-related to generate a key point set corresponding to the current tool center point.

[0129] Among them, the time-related is to match the posture coordinates and the force and moment data by using time sequence information, and the time sequence information is used to describe the time order of the key points, which is generated after interpolation by t∈[0, N]; the key point set contains the posture coordinates of the tool center point at any time and the corresponding force and moment vector information.

[0130] Among them, when the industrial robot receives the key point set, the key points will be processed according to the dynamics constraints of the robot, and an executable trajectory is generated by path planning or linear programming, thereby ensuring the smoothness and stability of the tool point when executing the path.

[0131] The present application effectively simplifies the teaching operation and reduces the position deviation in path generation, thereby significantly improving the overall precision and efficiency of the teaching process.

[0132] The tool point path assignment unit 5 is configured to perform step S5: tool point assignment to the key point set corresponding to the current tool center point, to complete the task path definition of the tool center point of the industrial robot.

[0133] Specifically, according to the time sequence information, the posture coordinates, forces and moments data in the current tool center point key point set are matched with the corresponding tool center point identification information and encoded into task instruction format, which is transmitted to the industrial robot to realize the task path definition of the tool center point.

[0134] The tool center point identification information is used to distinguish different end effectors in the industrial robot, and the task instruction format is an instruction data structure that can be directly recognized and executed by the industrial robot. The instruction data structures of different industrial robots may be different, and the present application does not specifically limit the matching design of the data structure.

[0135] Accordingly, based on the tool center point identification information, the present application ensures that the industrial robot can accurately assign the movement trajectory generated by path planning to the corresponding end effector after recognizing the task instruction, thereby ensuring that the movement trajectory of the tool center point strictly meets the requirements of the posture, force and moment in the key point set, and significantly improving the applicability and operation flexibility of the industrial robot in the multi-task and multi-tool scene, and effectively reducing the debugging complexity and the overall deployment cost of the robot.

[0136] Compared with the prior art, the present application adsorbs the magnetic drag teaching device to the tool center point (TCP) adjacent area of the industrial robot, directly uses the TCP calibration data for coordinate system conversion, effectively avoids the path error problem caused by distance deviation in the traditional rigid connection teaching device, and significantly improves the accuracy of TCP path planning and the reliability of the industrial robot in executing tasks.

[0137] In addition, the application generates a key point set by time stamp alignment, coordinate system conversion, interpolation smoothing and other processing on the teaching data, ensures the continuity and stability of the teaching data, and provides more accurate path key point input for the industrial robot, so that the industrial robot can autonomously complete path planning according to its own dynamic constraints, and improves the efficiency of the teaching process and the accuracy of task execution. Meanwhile, the application sequentially adsorbs multiple tool center points of the industrial robot by magnetic attraction dragging the teaching device, so as to allow the user to distribute the task path to multiple TCPs, and greatly enhances the flexibility and adaptability of the industrial robot in the multi-task and multi-tool scene.

[0138] Based on the same inventive concept, the application also provides an electronic device, which can be a server, a desktop computing device or a mobile computing device (for example, a laptop computer, a handheld computing device, a tablet computer, a netbook, etc.) or a terminal device. The device includes one or more processors and a memory, wherein the processor is used to execute a program to implement the control method of the industrial robot according to the embodiments of the application; and the memory is used to store a computer program executable by the processor.

[0139] Based on the same inventive concept, the application also provides a computer readable storage medium, which corresponds to the control method of the industrial robot according to any of the foregoing embodiments, and the computer readable storage medium has a computer program stored thereon, and the program is executed by a processor to implement the steps of the control method of the industrial robot according to any of the foregoing embodiments.

[0140] The application can adopt the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program codes. The computer readable storage medium includes permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0141] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, and the present application also intends to include these modifications and improvements.

Claims

1. A control method for an industrial robot, characterized in that, Includes the following steps: S1: Preprocess the dragging speed data from the magnetically attached teach pendant to obtain a set of dragging posture coordinates; wherein, the magnetically attached teach pendant is attached to the vicinity of the tool center point of an industrial robot, and is used to measure the dragging speed data and dragging torque set generated in three-dimensional space when the industrial robot is pulled by the magnetically attached teach pendant; the dragging speed data includes linear acceleration and angular velocity; the dragging torque set includes torque and linear force; S2: Align the timestamps of the dragged pose coordinate set and the dragged torque set to obtain the teaching data set; S3: Perform coordinate system transformation on the teaching data set based on the calibration data to obtain the dragging posture coordinate set and dragging torque set of the current tool center point; Includes the following sub-steps: S31: Based on the translation and rotation matrices in the calibration data, perform coordinate system transformation on the dragging posture coordinate set in the teaching data set to obtain the dragging posture coordinate set of the current tool center point, as shown below: In the formula, This represents the set of draggage coordinates for the current tool point, i.e., TCP. This represents the result after the position coordinate transformation. It is a translation matrix; It is a rotation matrix; For the first The dragging attitude coordinates of the magnetically dragged teach pendant in the coordinate system at any given time consist of three components. ; For the first The rotation angle of the teach pendant in the coordinate system is determined by the magnetic dragging mechanism, and includes three components. ; S32: Based on the rotation matrix in the calibration data, perform coordinate transformation on the dragging torque set in the teaching data set to obtain the dragging posture coordinate set of the current tool center point, as shown below: In the formula, This represents the set of dragging torques at the current tool's center point; For the first The set of force vectors in the coordinate system of the magnetically dragged teach pendant at any given moment represents the... Linear force in the direction; For the first The set of torque vectors in the coordinate system of the magnetically dragged teach pendant at any given moment represents the... Torque data in the direction; S4: Interpolate the set of dragging posture coordinates and dragging torque of the current tool center point to obtain the set of key points corresponding to the current tool center point; S5: Assign tool points to the key point set corresponding to the current tool center point, and complete the task path definition for the corresponding tool center point of the industrial robot; The specific representation of the dragging posture coordinate set is as follows: In the formula, This indicates the set of attitude coordinates to be dragged. They are respectively represented as The magnetic drag-and-drop teach pendant at the moment The position coordinates in the direction are obtained by numerically integrating the linear acceleration in three-dimensional space, as shown in the following calculation: In the formula, express The magnetic drag-and-drop teach pendant at the moment Linear acceleration on the axis; These are the initial position coordinates of the teach pendant; respectively The magnetic drag-and-drop teach pendant at the moment The rotation angle on the axis is obtained by numerically integrating the angular velocity in three-dimensional space, and the specific calculation is expressed as follows: In the formula, express Angular velocity data in three-dimensional space measured at any given time; This is the initial rotation angle of the teach pendant; For timestamps, This indicates the longest time a user can drag the teach pendant using the magnetic attachment.

2. The control method for an industrial robot according to claim 1, characterized in that, Step S4 includes the following sub-steps: S41: Use spline interpolation to interpolate the dragging attitude coordinate set of the current center point to obtain a smooth dragging attitude coordinate set; S42: Based on the smooth set of dragging posture coordinates, spline interpolation is used to interpolate the set of dragging torques, and a low-pass filter is used to smooth the interpolated set of dragging torques to obtain a smooth set of dragging torques. S43: Time-correlate the smooth dragging posture coordinate set with the dragging torque set to generate the key point set corresponding to the current tool center point.

3. A control device for an industrial robot, characterized in that, It includes a drag speed data preprocessing unit, a data timestamp alignment unit, a coordinate system transformation unit, a path planning unit, and a tool point path allocation unit; The drag speed data preprocessing unit is used to preprocess the drag speed data from the magnetic drag teach pendant to obtain a drag posture coordinate set. The magnetic drag teach pendant is attached to the vicinity of the tool center point of an industrial robot and is used to measure the drag speed data and drag torque set generated in three-dimensional space when the industrial robot is pulled by the magnetic drag teach pendant. The drag speed data includes linear acceleration and angular velocity; the drag torque set includes torque and linear force. The data timestamp alignment unit is used to align the drag pose coordinate set and the drag torque set with timestamps to obtain the teaching data set. The coordinate system transformation unit is used to perform coordinate system transformation on the teaching data set according to the calibration data to obtain the dragging posture coordinate set and dragging torque set of the current tool center point; the coordinate system transformation unit is also used to perform the following sub-steps: Based on the translation and rotation matrices in the calibration data, a coordinate system transformation is performed on the dragging posture coordinate set in the teaching data set to obtain the dragging posture coordinate set of the current tool center point, as shown below: In the formula, This represents the set of draggage coordinates for the current tool point, i.e., TCP. This represents the result after the position coordinate transformation. It is a translation matrix; It is a rotation matrix; For the first The dragging attitude coordinates of the magnetically dragged teach pendant in the coordinate system at any given time consist of three components. ; For the first The rotation angle of the teach pendant in the coordinate system is determined by the magnetic dragging mechanism, and includes three components. ; S32: Based on the rotation matrix in the calibration data, perform coordinate transformation on the dragging torque set in the teaching data set to obtain the dragging posture coordinate set of the current tool center point, as shown below: In the formula, This represents the set of dragging torques at the current tool's center point; For the first The set of force vectors in the coordinate system of the magnetically dragged teach pendant at any given moment represents the... Linear force in the direction; For the first The set of torque vectors in the coordinate system of the magnetically dragged teach pendant at any given moment represents the... Torque data in the direction; The path planning unit is used to interpolate the set of dragging posture coordinates and the set of dragging torque of the current tool center point to obtain the set of key points corresponding to the current tool center point. The tool point path allocation unit is used to allocate tool points to the key point set corresponding to the current tool center point, thereby completing the task path definition for the corresponding tool center point of the industrial robot. The specific representation of the dragging posture coordinate set is as follows: In the formula, This indicates the set of attitude coordinates to be dragged. They are respectively represented as The magnetic drag-and-drop teach pendant at the moment The position coordinates in the direction are obtained by numerically integrating the linear acceleration in three-dimensional space, as shown in the following calculation: In the formula, express The magnetic drag-and-drop teach pendant at the moment Linear acceleration on the axis; These are the initial position coordinates of the teach pendant; respectively The magnetic drag-and-drop teach pendant at the moment The rotation angle on the axis is obtained by numerically integrating the angular velocity in three-dimensional space, and the specific calculation is expressed as follows: In the formula, express Angular velocity data in three-dimensional space measured at any given time; This is the initial rotation angle of the teach pendant; For timestamps, This indicates the longest time a user can drag the teach pendant using the magnetic attachment.

4. A control system for an industrial robot, characterized in that, Includes a magnetically draggable teach pendant and control device; The magnetically attached teach pendant is magnetically attached to the vicinity of the tool center point of an industrial robot and communicates with the control device. It is used to measure the attitude speed and torque changes of the magnetically attached teach pendant in three-dimensional space, thereby obtaining the drag speed data and drag torque set, and inputting them to the control device. The magnetically attached teach pendant includes a drag handle, a six-dimensional force sensor, a six-axis sensor, and an electromagnet that are stacked and fixedly connected in sequence. The drag handle is used to displace the tool center point of the industrial robot under external force. The six-dimensional force sensor is used to measure the linear force and torque generated in three-dimensional space, convert them into electrical signals, form a set of drag torques, and input them to the control device. The six-axis sensor includes three accelerometers and three gyroscopes, used to measure linear acceleration and angular velocity in three-dimensional space, and input them to the control device as drag speed data; The electromagnet generates magnetic force through an electrical connection, which is used to attract and fix the area near the tool center point of the industrial robot by magnetic force. The control device is the control device for the industrial robot described in claim 3.

5. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements a control method for an industrial robot as described in any one of claims 1-2.

6. A computer-readable storage medium storing computer-executable instructions, characterized in that, When the computer-executable instructions are executed by the processor, the control method for the industrial robot as described in any one of claims 1-2 is implemented.

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