Parallel robot dynamic contour error pre-compensation method and device

Abstract

The application discloses a parallel robot dynamic contour error pre-compensation method and device, wherein the method comprises the following steps: acquiring the dynamic parameters of a parallel machining robot, and determining the rigid body dynamics model of the parallel machining robot; based on the preset rigid body dynamics model, the theoretical driving force of each driving shaft of the parallel machining robot is calculated and input to the torque feedforward channel of a servo driving system to perform dynamics feedforward control; by using a pre-constructed tracking error estimation model of the driving shaft of the parallel machining robot, the dynamic contour error of tool movement is estimated, and the motion trajectory is corrected in the task space according to the dynamic contour error, so as to perform high dynamic precision control on the parallel machining robot. Thus, the problem that the dynamic precision and machining quality of the robot are difficult to guarantee due to the mismatch between the controller performance and the nonlinear dynamics characteristics and nonlinear friction force characteristics of the controlled object, i.e., the parallel machining robot, in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of robotics and application technology, and in particular to a method and apparatus for pre-compensation of dynamic contour error of a parallel robot. Background Technology

[0002] In related technologies, due to the strict sealing of the drive unit and hinge, the robot will have a large frictional resistance during movement. Combined with the influence of the nonlinear dynamic characteristics of the robot body, it is difficult to guarantee the dynamic accuracy of the robot during movement. Therefore, the dynamic accuracy of the robot can be controlled by using a conventional three-loop PID (proportional-integral-derivative) controller to reduce the dynamic error when the drive axis changes direction.

[0003] However, in related technologies, the mismatch between the controller performance and the nonlinear dynamic and nonlinear frictional characteristics of the parallel processing robot makes it difficult to achieve satisfactory control effects, resulting in difficulties in ensuring the dynamic accuracy and processing quality of the robot, which urgently needs to be solved. Summary of the Invention

[0004] This application is based on the inventor's understanding and insights into the following issues:

[0005] In major technological fields such as aerospace and energy, as design levels become increasingly mature and the complexity of components continues to rise, stringent requirements are placed on the performance of machining equipment in compound angle machining and high-precision machining. Parallel machining robots can avoid singular domains within the posture workspace by rationally configuring the mechanism configuration, and can serve as an effective supplement to traditional serial machine tools, applied to the machining of complex components with complex curved surface features.

[0006] Because the robot's end effector has complex motion patterns during operation, it needs to adjust its position and attitude simultaneously, resulting in frequent acceleration, deceleration, and reversal of the drive shaft. In addition, cutting fluid and chips are usually splashed during the machining process. To protect the equipment, the drive unit and hinges are usually strictly sealed, which leads to a large frictional resistance during the robot's movement. Combined with the influence of the robot's nonlinear dynamic characteristics, it is difficult to guarantee the dynamic accuracy of the robot during movement, especially when the drive shaft is reversing, resulting in a large dynamic error that affects the machining accuracy.

[0007] Existing technologies typically employ conventional three-loop PID controllers to control the dynamic accuracy of robots. However, due to the mismatch between the controller's performance and the nonlinear dynamic and nonlinear frictional characteristics of the robot being processed in parallel, it is difficult to achieve satisfactory control results, and improvements are urgently needed.

[0008] This application provides a method and apparatus for pre-compensation of dynamic contour error of parallel robots, in order to solve the problem in related technologies that the dynamic accuracy and processing quality of the robot are difficult to guarantee due to the mismatch between the performance of the controller and the nonlinear dynamic characteristics and nonlinear friction characteristics of the parallel processing robot of the controlled object.

[0009] The first aspect of this application provides a method for pre-compensating dynamic contour errors of a parallel robot, comprising the following steps: acquiring the dynamic parameters of the parallel machining robot and determining the rigid body dynamics model of the parallel machining robot; calculating the theoretical driving force of each drive axis of the parallel machining robot based on the preset rigid body dynamics model, and inputting the theoretical driving force into the torque feedforward channel of the servo drive system for dynamic feedforward control; using a pre-constructed tracking error prediction model of the drive axes of the parallel machining robot to predict the dynamic contour error of the tool movement, and correcting the motion trajectory in the task space according to the dynamic contour error, so as to perform high dynamic precision control on the parallel machining robot.

[0010] Optionally, in one embodiment of this application, before estimating the dynamic contour error of the tool movement, the system further includes: a single-degree-of-freedom servo drive system based on multiple time-varying loads determined by the parallel machining robot, wherein the position loop of the single-degree-of-freedom servo drive system adopts a proportional controller, the speed loop adopts a proportional-integral controller, and the current loop adopts a proportional controller. The controlled object is a motor rotor, which acts as a first-order inertial element. The time-varying load caused by the movement of the mechanical body of the parallel machining robot acts on the output end of the current loop as a disturbance of the control system. A speed feedforward is added to the input port of the speed loop, and a torque feedforward is added to the input port of the current loop.

[0011] Based on the single-degree-of-freedom servo drive control system, the dynamic error transfer function is derived as follows:

[0012] E(s)=E load (s)+E input (s)=G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)

[0013] Among them, E load (s) is the primary source, E input (s) is the second source, G eload (s) is the error transfer function from the first source, G einput (s) is the error transfer function from the second source, K t T is the torque coefficient of the current loop.ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop, Q d (s) represents the motion command input to the drive shaft;

[0014] A tracking error prediction model for the drive axis of the parallel processing robot is established to determine the sources of tracking error. The sources of tracking error include a first source caused by the dynamic characteristics of the parallel processing robot and a second source caused by the characteristics of the motor closed-loop feedback control system.

[0015] The first source is:

[0016] E load (s)=G eload (s)(K t T ff (s)-T L (s))

[0017] Among them, G eload (s) is the error propagation function from the first source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop.

[0018] The second source is:

[0019] E input (s)=G einput (s)Q d (s)

[0020] Among them, G einput (s) is the error transfer function from the second source, Q d (s) is the motion command input to the drive shaft.

[0021] Optionally, in one embodiment of this application, after determining the source of the tracking error, the method further includes: generating a dynamic precision control strategy based on the source of the tracking error, which combines dynamic feedforward and dynamic tracking error pre-compensation methods. The dynamic precision control strategy includes using a target dynamic feedforward control method to eliminate dynamic errors caused by robot dynamic characteristics and using a target dynamic tracking error pre-compensation method to compensate for dynamic tracking errors caused by the characteristics of the motor closed-loop feedback control system.

[0022] Optionally, in one embodiment of this application, the tracking error prediction model is:

[0023]

[0024] in, K is the estimated value of the dynamic tracking error caused by the characteristics of the closed-loop feedback system. ev For the speed term prediction coefficient, K is the speed of motion input to the drive shaft. ea For the acceleration term prediction coefficient, This is the motion acceleration input to the drive shaft.

[0025] Optionally, in one embodiment of this application, the step of using a pre-built tracking error prediction model for the drive axis of a parallel machining robot to predict the dynamic contour error of the tool movement and correcting the motion trajectory in the task space based on the dynamic contour error includes: obtaining the command trajectory of the robot end-effector tool of the parallel machining robot; converting the reference motion trajectory of the robot end-effector tool into a reference motion trajectory of the drive axis, and obtaining the predicted tracking error value of the drive axis based on the tracking error prediction model; predicting the actual motion trajectory reached by the tool, and obtaining the dynamic contour error based on the reference motion trajectory and the predicted motion trajectory actually reached by the tool, wherein predicting the actual motion trajectory reached by the tool and obtaining the dynamic contour error based on the reference motion trajectory and the predicted motion trajectory actually reached by the tool includes solving the contour error by finding the contour error point of the curved path, wherein solving the contour error by finding the contour error point of the curved path includes using a lookup table method to search for the point on the expected trajectory that is closest to the actual position. Since the contour error point is in a small neighborhood of the point with the smallest distance, the parameterized spline curve is Taylor expanded at the point with the smallest distance, and the calculation formula of the contour error point of the curved path is:

[0026]

[0027] Among them, P fi For the contour error point, P qi Let u be the point on the desired trajectory that is closest to the actual position, Δu be the spline parameter of the curve path, Δu be the differential of the spline parameter, and o be a higher-order infinitesimal term.

[0028] By differentiating the spline parameters, the tangent direction of the spline curve at the contour error point is obtained as follows:

[0029] P' fi =P' qi (u)+P” qi (u)Δu

[0030] An equation is constructed based on geometric relations to solve for the differential of the spline parameters at the foot of the perpendicular, wherein the geometric relations are:

[0031] (P ai -P fi )·P'fi =0

[0032] Among them, P ai P' is the distance from the actual position on the desired trajectory. fi This represents the direction of the tangent to the spline curve at the point of profile error.

[0033] The equation is as follows:

[0034]

[0035] Then, the cubic equation in one variable is solved to obtain the differential of the spline parameters, and the coordinates of the contour error points and the spline parameters are calculated, wherein the spline parameters are:

[0036] u f =u+Δu

[0037] The dynamic contour error is calculated as follows:

[0038] ε i =P fi -P ai

[0039] Where, ε i This refers to the contour error.

[0040] Optionally, in one embodiment of this application, the step of correcting the motion trajectory in the task space based on the dynamic contour error includes: performing contour error pre-compensation using a mirror method based on the dynamic contour error to obtain a corrected tool motion trajectory, thereby obtaining a corrected drive axis motion trajectory, and sending the corrected drive axis motion trajectory to the controller for execution, wherein the corrected drive axis motion trajectory is:

[0041] P ci =P ai +t i +ε i ,

[0042] Among them, P ci To determine the compensated tool tip position, P ai ε is the distance from the actual position on the desired trajectory. i The profile error of the tool motion, t i This represents the tracking error of the tool movement.

[0043] A second aspect of this application provides a dynamic contour error pre-compensation device for a parallel robot, comprising: an acquisition module for acquiring dynamic parameters of the parallel machining robot and determining the rigid body dynamics model of the parallel machining robot; a calculation module for calculating the theoretical driving force of each drive axis of the parallel machining robot based on the preset rigid body dynamics model, and inputting the theoretical driving force into the torque feedforward channel of the servo drive system for dynamic feedforward control; and an estimation module for estimating the dynamic contour error of the tool movement using a pre-constructed tracking error estimation model of the drive axes of the parallel machining robot, and correcting the motion trajectory in the task space according to the dynamic contour error, so as to perform high dynamic precision control on the parallel machining robot.

[0044] Optionally, in one embodiment of this application, the apparatus further includes: a setup module, configured to, before estimating the dynamic contour error of the tool movement, establish a single-degree-of-freedom servo drive system under multiple time-varying loads determined by the parallel machining robot, wherein the position loop of the single-degree-of-freedom servo drive system uses a proportional controller, the velocity loop uses a proportional-integral controller, and the current loop uses a proportional controller; the controlled object is a motor rotor, which serves as a first-order inertial element; the time-varying load caused by the mechanical body movement of the parallel machining robot acts on the output of the current loop as a disturbance to the control system; a velocity feedforward is added to the input of the velocity loop, and a torque feedforward is added to the input of the current loop; wherein, based on the single-degree-of-freedom servo drive control system, the dynamic error transfer function is derived as follows:

[0045] E(s)=E load (s)+E input (s)=G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)

[0046] Among them, E load (s) is the primary source, E input (s) is the second source, G eload (s) is the error transfer function from the first source, G einput (s) is the error transfer function from the second source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop, Q d (s) represents the motion command input to the drive shaft.

[0047] A tracking error prediction model for the drive axis of the parallel machining robot is established to determine the sources of tracking error. These sources include a first source caused by the dynamic characteristics of the parallel machining robot and a second source caused by the characteristics of the motor closed-loop feedback control system.

[0048] The first source is:

[0049] E load (s)=G eload (s)(K t T ff (s)-T L (s))

[0050] Among them, G eload (s) is the error propagation function from the first source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop.

[0051] The second source is:

[0052] E input (s)=G einput (s)Q d (s)

[0053] Among them, G einput (s) is the error transfer function from the second source, Q d (s) is the motion command input to the drive shaft.

[0054] Optionally, in one embodiment of this application, the apparatus of this embodiment further includes: a generation module, configured to, after determining the source of the tracking error, generate a dynamic precision control strategy that combines dynamic feedforward and dynamic tracking error pre-compensation method based on the source of the tracking error, wherein the dynamic precision control strategy includes using a target dynamic feedforward control method to eliminate dynamic errors caused by robot dynamic characteristics and using a target dynamic tracking error pre-compensation method to compensate for dynamic tracking errors caused by the characteristics of the motor closed-loop feedback control system.

[0055] Optionally, in one embodiment of this application, the tracking error prediction model is:

[0056]

[0057] in, K is the estimated value of the dynamic tracking error caused by the characteristics of the closed-loop feedback system. ev For the speed term prediction coefficient, K is the speed of motion input to the drive shaft.ea For the acceleration term prediction coefficient, This is the motion acceleration input to the drive shaft.

[0058] Optionally, in one embodiment of this application, the estimation module includes: a first acquisition unit, used to acquire the command trajectory of the robot end-effector of the parallel machining robot; a conversion unit, used to convert the reference motion trajectory of the robot end-effector into a reference motion trajectory of the drive axis, and obtain the tracking error prediction value of the drive axis according to the tracking error estimation model; a second acquisition unit, used to estimate the actual motion trajectory reached by the tool, and obtain the dynamic contour error according to the reference motion trajectory and the estimated motion trajectory actually reached by the tool, wherein the estimation of the actual motion trajectory reached by the tool, and obtaining the dynamic contour error according to the reference motion trajectory and the estimated motion trajectory actually reached by the tool, includes solving the contour error by finding the contour error point of the curve path, wherein the solution of the contour error by finding the contour error point of the curve path includes using a lookup table method to search for the point on the expected trajectory that is closest to the actual position. Since the contour error point is in a small neighborhood of the smallest point, the parameterized spline curve is Taylor expanded at the smallest point, and the calculation formula of the contour error point of the curve path is:

[0059]

[0060] Among them, P fi For the contour error point, P qi Let u be the point on the desired trajectory that is closest to the actual position, Δu be the spline parameter of the curve path, Δu be the differential of the spline parameter, and o be a higher-order infinitesimal term.

[0061] By differentiating the spline parameters, the tangent direction of the spline curve at the contour error point is obtained as follows:

[0062] P' fi =P' qi (u)+P” qi (u)Δu

[0063] An equation is constructed based on geometric relations to solve for the differential of the spline parameters at the foot of the perpendicular, wherein the geometric relations are:

[0064] (P ai -P fi )·P' fi =0

[0065] The equation is as follows:

[0066]

[0067] Then, the cubic equation in one variable is solved to obtain the differential of the spline parameters, and the coordinates of the contour error points and the spline parameters are calculated, wherein the spline parameters are:

[0068] u f =u+Δu

[0069] The dynamic contour error is calculated as follows:

[0070] ε i =P fi -P ai

[0071] Where, ε i This refers to the contour error.

[0072] Optionally, in one embodiment of this application, the estimation module includes: a third acquisition unit, configured to perform contour error pre-compensation using a mirror method based on the dynamic contour error to obtain a corrected tool motion trajectory, thereby obtaining a corrected drive shaft motion trajectory, and sending the corrected drive shaft motion trajectory to the controller for execution, wherein the corrected drive shaft motion trajectory is:

[0073] P ci =P ai +t i +ε i ,

[0074] Among them, P ci To determine the compensated tool tip position, P ai ε is the distance from the actual position on the desired trajectory. i The profile error of the tool motion, t i This represents the tracking error of the tool movement.

[0075] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the parallel robot dynamic contour error pre-compensation method as described in the above embodiments.

[0076] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for pre-compensating dynamic contour errors in a parallel robot.

[0077] This application's embodiments can determine a rigid body dynamics model based on the dynamic parameters of a parallel machining robot, thereby calculating the theoretical driving force of each drive axis of the parallel machining robot and inputting it into the torque feedforward channel of the servo drive system for dynamic feedforward control. Utilizing a pre-constructed tracking error prediction model of the parallel machining robot's drive axes, the dynamic contour error of the tool movement is predicted, and the motion trajectory is corrected within the task space. This enables high-dynamic-precision control of the parallel machining robot, effectively improving the robot's dynamic accuracy and machining quality. Therefore, it solves the problem in related technologies where the mismatch between the controller performance and the nonlinear dynamic and nonlinear frictional characteristics of the controlled object (parallel machining robot) makes it difficult to guarantee the robot's dynamic accuracy and machining quality.

[0078] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0079] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0080] Figure 1 This is a flowchart of a method for pre-compensating dynamic contour errors of a parallel robot according to an embodiment of this application;

[0081] Figure 2 This is a schematic diagram illustrating the dynamic contour error pre-compensation principle of a specific embodiment of this application;

[0082] Figure 3 This is a schematic diagram of a wavy path and the corresponding feed rate at each point on the path, representing a specific embodiment of this application.

[0083] Figure 4 This is a schematic diagram of the command trajectory of a robot end effector according to a specific embodiment of this application.

[0084] Figure 5 This is a schematic diagram of the dynamic tracking error prediction curve of the drive axis when a robot tracks a wavy path according to a specific embodiment of this application.

[0085] Figure 6 This is a schematic diagram of the tracking error prediction curve at the end of the tool when tracking a wavy curve according to a specific embodiment of this application;

[0086] Figure 7 This is a schematic diagram of the contour error prediction curve when the tool tracks a wavy path according to a specific embodiment of this application.

[0087] Figure 8This is a schematic diagram of a contour error prediction model according to a specific embodiment of this application;

[0088] Figure 9 This is a schematic diagram of the principle of a single-axis servo drive control system under time-varying load according to a specific embodiment of this application;

[0089] Figure 10 This is a schematic diagram of the structure of the parallel robot dynamic contour error pre-compensation device provided in the embodiments of this application;

[0090] Figure 11 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0091] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0092] The following description, with reference to the accompanying drawings, illustrates a method and apparatus for pre-compensating dynamic contour errors in parallel robots according to embodiments of this application. Addressing the problem mentioned in the background art where the mismatch between controller performance and the nonlinear dynamic and frictional characteristics of the parallel machining robot leads to difficulties in guaranteeing the robot's dynamic accuracy and machining quality, this application provides a method for pre-compensating dynamic contour errors in parallel robots. In this method, a rigid body dynamics model can be determined based on the dynamic parameters of the parallel machining robot, thereby calculating the theoretical driving force of each drive axis of the parallel machining robot and inputting it into the torque feedforward channel of the servo drive system for dynamic feedforward control. Using a pre-constructed tracking error prediction model of the parallel machining robot's drive axes, the dynamic contour error of the tool movement is predicted, and the motion trajectory is corrected within the task space to achieve high dynamic precision control of the parallel machining robot, effectively improving the robot's dynamic accuracy and machining quality. This solves the problem in the related art where the mismatch between controller performance and the nonlinear dynamic and frictional characteristics of the parallel machining robot leads to difficulties in guaranteeing the robot's dynamic accuracy and machining quality.

[0093] Specifically, Figure 1 This is a flowchart illustrating a method for pre-compensation of dynamic contour error in a parallel robot, as provided in an embodiment of this application.

[0094] like Figure 1 As shown, the method for pre-compensating dynamic contour errors of the parallel robot includes the following steps:

[0095] In step S101, the dynamic parameters of the parallel processing robot are obtained, and the rigid body dynamic model of the parallel processing robot is determined.

[0096] It is understood that the embodiments of this application can obtain the dynamic parameters of the parallel processing robot. For example, the dynamic parameters of the parallel robot can be identified, and the rigid body dynamic model of the parallel processing robot can be determined, thereby effectively improving the feasibility of dynamic contour error pre-compensation of the parallel robot.

[0097] In step S102, based on the preset rigid body dynamics model, the theoretical driving force of each drive axis of the parallel processing robot is calculated, and the theoretical driving force is input into the torque feedforward channel of the servo drive system for dynamic feedforward control.

[0098] It is understood that the embodiments of this application can calculate the theoretical driving force of each drive axis of the parallel processing robot in real time based on the rigid body dynamics model, and input the theoretical driving force into the torque feedforward channel of the servo drive system to complete the dynamic feedforward control, effectively reducing the dynamic tracking error.

[0099] Furthermore, with feedforward processing of machining dynamics, the dynamic tracking error caused by the nonlinear dynamic characteristics and nonlinear friction of the robot is greatly reduced. The dynamic error of each drive axis during the robot's movement is dominated by the tracking error caused by the characteristics of the closed-loop feedback control system. The tracking error is linearly related to the speed and acceleration of the drive axis, and can be accurately predicted before the actual movement.

[0100] In step S103, the dynamic contour error of the tool movement is estimated by using a pre-built tracking error prediction model of the parallel machining robot drive axis, and the motion trajectory is corrected in the task space according to the dynamic contour error, so as to perform high dynamic precision control on the parallel machining robot.

[0101] It is understood that the embodiments of this application can utilize the pre-built tracking error prediction model of the parallel machining robot drive axis in the following steps to predict the dynamic contour error of the tool movement, and correct the motion trajectory in the task space according to the dynamic contour error, thereby performing high dynamic precision control on the parallel machining robot, effectively improving the dynamic precision of the robot and improving the machining quality.

[0102] In one embodiment of this application, a pre-built tracking error prediction model for the drive axis of a parallel machining robot is used to predict the dynamic contour error of the tool movement, and the motion trajectory is corrected in the task space based on the dynamic contour error. This includes: obtaining the command trajectory of the robot end-effector tool of the parallel machining robot; converting the reference motion trajectory of the robot end-effector tool into a reference motion trajectory of the drive axis, and obtaining the predicted tracking error value of the drive axis based on the tracking error prediction model; predicting the actual motion trajectory reached by the tool, and obtaining the dynamic contour error based on the reference motion trajectory and the predicted actual motion trajectory reached by the tool. The prediction of the actual motion trajectory reached by the tool and the obtaining of the dynamic contour error based on the reference motion trajectory and the predicted actual motion trajectory reached by the tool include solving for the contour error by finding the contour error point of the curved path. Solving for the contour error by finding the contour error point of the curved path includes using a lookup table method to search for the point on the desired trajectory that is closest to the actual position. Since the contour error point is within a small neighborhood of the smallest point, the parameterized spline curve is Taylor expanded at the smallest point to obtain the calculation formula for the contour error point of the curved path.

[0103]

[0104] Among them, P fi For the contour error point, P qi Let u be the point on the desired trajectory that is closest to the actual position, Δu be the spline parameter of the curve path, Δu be the differential of the spline parameter, and o be a higher-order infinitesimal term.

[0105] By using differentiation to find the spline parameters, the tangent direction of the spline curve at the contour error point is obtained as follows:

[0106] P' fi =P' qi (u)+P” qi (u)Δu

[0107] Equations are constructed based on geometric relationships to solve for the differential of the spline parameters at the foot of the perpendicular, where the geometric relationships are:

[0108] (P ai -P fi )·P' fi =0

[0109] The equation is:

[0110]

[0111] Then, solve the cubic equation in one variable to obtain the differential of the spline parameters, and calculate the coordinates of the contour error points and the spline parameters, where the spline parameters are:

[0112] u f =u+Δu

[0113] The dynamic profile error is calculated as follows:

[0114] ε i =P fi -P ai

[0115] Where, ε i This refers to the contour error.

[0116] For example, such as Figure 2 The diagram shown illustrates the principle of dynamic contour error pre-compensation according to a specific embodiment of this application. This embodiment can obtain the command trajectory of the robot's end-effector tool for wavy machining paths through machining trajectory planning. Specifically, as shown... Figure 3 and Figure 4 As shown, where, Figure 3 The wavy machining path and the corresponding feed rate f at each point on the path are given. Figure 4 The command trajectory of the robot's end effector includes the command position p, command velocity v, and command acceleration a.

[0117] Next, the command trajectory of the robot's end effector can be converted to the drive axis space to obtain the command trajectory of the drive axis, which may include the drive axis position L. r (t), drive shaft speed Drive shaft acceleration like Figure 5 As shown, based on the dynamic tracking error prediction model for the drive shafts in the following steps, the predicted dynamic tracking error value for each drive shaft can be obtained.

[0118] Secondly, such as Figure 6 As shown, the actual curve P reached by the tool can be obtained from the forward kinematics solution of the robot. a (t), thus obtaining the tool tracking error curve.

[0119] Optionally, in one embodiment of this application, correcting the motion trajectory in the task space based on the dynamic contour error includes: performing contour error pre-compensation using a mirror method based on the dynamic contour error to obtain a corrected tool motion trajectory, thereby obtaining a corrected drive shaft motion trajectory, and sending the corrected drive shaft motion trajectory to the controller for execution, wherein the corrected drive shaft motion trajectory is:

[0120] P ci =P ai +t i +ε i ,

[0121] Among them, P ci To determine the compensated tool tip position, P ai ε is the distance from the actual position on the desired trajectory.i The profile error of the tool motion, t i This represents the tracking error of the tool movement.

[0122] For example, such as Figure 7 As shown, based on the contour error calculation method, the contour error can be calculated and the estimated contour error value when the tool tracks the wavy curve can be obtained, as well as the curve of the estimated contour error value changing with time.

[0123] Based on the contour error, the mirror method is used to determine the end motion trajectory P. r (t) is compensated to obtain the corrected end-effector trajectory P. c (t), where:

[0124] P ci =P ai +t i +ε i ,

[0125] Among them, P ci To determine the compensated tool tip position, P ai ε is the distance from the actual position on the desired trajectory. i The profile error of the tool motion, t i This represents the tracking error of the tool movement.

[0126] Furthermore, by using the modified end effector trajectory to control the robot's motion, the tool's motion trajectory can be corrected within the task space, thereby achieving high-speed and high-precision motion control at the end effector.

[0127] In some embodiments, the specific process of obtaining the contour error of the end effector based on the tool reference motion trajectory and the tool estimated motion trajectory is as follows.

[0128] like Figure 8 As shown, embodiments of this application can establish a contour error prediction model. Figure 8 (1) The line in the diagram represents the desired curved path, and the actual path reached by the tip of the knife is... Figure 8 In curve (2), at a certain moment, the reference point that the tool expects to reach is P. di The actual location reached is P in the diagram. ai Then P ai P di The vector t between i The tracking error of the tool motion is the distance P along the desired path. ai The nearest point is the contour error point P. fi P ai P fi The vector ε between i This refers to the contour error.

[0129] The key to solving the contour error lies in finding the contour error point P of the curved path. fi The specific steps are as follows:

[0130] (1) Use the table lookup method to search for the distance P from the actual position on the expected trajectory. ai The smallest point P qi ;

[0131] (2) Due to the contour error point P fi In P qi Within a small neighborhood, the parameterized spline curve P(u) can be represented in P qi Performing a Taylor expansion at point P yields P fi The calculation formula is as follows:

[0132]

[0133] Among them, P fi For the contour error point, P qi Let u be the point on the desired trajectory that is closest to the actual position, Δu be the spline parameter of the curve path, Δu be the differential of the spline parameter, and o be a higher-order infinitesimal term.

[0134] (3) Construct equations to solve for the spline parameters and the perpendicular foot point.

[0135] Differentiating the above formula with respect to Δu, we can obtain the spline curve at P. fi Tangent direction at:

[0136] P' fi =P' qi (u)+P” qi (u)Δu,

[0137] According to geometric relations (P) ai -P fi )·P' fi =0 can be used to establish the following equation to find the Δu at the foot of the perpendicular:

[0138]

[0139] Next, by solving the cubic equation, we can obtain Δu, and thus solve for the spline parameter u of the contour error point. f =u+Δu and the coordinates P of the contour error point fi Then, the contour error ε can be solved. i :

[0140] ε i =P fi -P ai

[0141] Where, ε i This refers to the contour error.

[0142] Optionally, in one embodiment of this application, before estimating the dynamic contour error of the tool movement, the system further includes: a single-degree-of-freedom servo drive system under multiple time-varying loads determined by the parallel machining robot, wherein the position loop of the single-degree-of-freedom servo drive system adopts a proportional controller, the speed loop adopts a proportional-integral controller, and the current loop adopts a proportional controller. The controlled object is a motor rotor, which acts as a first-order inertial element. The time-varying load caused by the movement of the mechanical body of the parallel machining robot acts on the output end of the current loop as a disturbance of the control system. A speed feedforward is added to the input port of the speed loop, and a torque feedforward is added to the input port of the current loop.

[0143] Based on the single-degree-of-freedom servo drive control system, the dynamic error transfer function is derived as follows:

[0144] E(s)=E load (s)+E input (s)=G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s),

[0145] Among them, E load (s) is the primary source, E input (s) is the second source, G eload (s) is the error transfer function from the first source, G einput (s) is the error transfer function from the second source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop, Q d (s) represents the motion command input to the drive shaft;

[0146] A tracking error prediction model for the drive axis of a parallel machining robot is established to determine the sources of tracking error. The sources of tracking error include a first source caused by the dynamic characteristics of the parallel machining robot and a second source caused by the characteristics of the motor closed-loop feedback control system.

[0147] The primary source is:

[0148] E load (s)=G eload (s)(K t T ff (s)-T L (s)),

[0149] Among them, G eload(s) is the error propagation function from the first source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop.

[0150] The second source is:

[0151] E input (s)=G einput (s)Q d (s),

[0152] Among them, G einput (s) is the error transfer function from the second source, Q d (s) is the motion command input to the drive shaft.

[0153] As one possible approach, this application embodiment can treat the parallel machining robot as a single-degree-of-freedom servo drive system under multiple time-varying loads, and establish a tracking error prediction model for the drive axis of the parallel machining robot. According to the tracking error prediction model, the tracking error of the drive axis of the parallel robot mainly includes two sources: one is caused by the nonlinear dynamic characteristics and nonlinear friction of the robot, and the other is caused by the characteristics of the closed-loop feedback control system, thereby improving the feasibility of dynamic contour error pre-compensation for the parallel robot.

[0154] For example, such as Figure 9 As shown, in this embodiment of the application, the parallel machining robot can be used as a single-axis servo drive system under five time-varying loads. Figure 9 For each single-axis servo drive control system, the basic control architecture is a conventional three-loop PID control. The position loop uses a proportional controller, the speed loop uses a proportional-integral controller, and the current loop uses a proportional controller. The controlled object is the motor rotor, which can be used as a first-order inertial element. The time-varying load caused by the movement of the robot's mechanical body acts on the output of the current loop and can be used as a disturbance of the control system. In order to improve the response rate of the servo system, a speed feedforward can be added to the input of the speed loop and a torque feedforward can be added to the input of the current loop.

[0155] Next, the dynamic error transfer function can be derived based on the block diagram of the servo drive control system:

[0156] E(s)=E load (s)+E input (s)=G eload (s)(K t T ff (s)-T L (s))+G einput(s)Q d (s),

[0157] Therefore, the dynamic tracking error of the servo drive system has two sources. The first source is the tracking error caused by the time-varying load:

[0158] E load (s)=G eload (s)(K t T ff (s)-T L (s)),

[0159] Among them, G eload (s) is the error propagation function for this part, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop.

[0160] The second source is the dynamic tracking error caused by the characteristics of the closed-loop feedback control system:

[0161] E input (s)=G einput (s)Q d (s),

[0162] Among them, G einput (s) is the error propagation function for this part, Q d (s) is the motion command input to the drive shaft.

[0163] The second source of dynamic tracking error is related to the motion command input to the drive shaft. The dynamic tracking error prediction model can be summarized into the following time-domain equation:

[0164]

[0165] in, K is the estimated value of the dynamic tracking error caused by the characteristics of the closed-loop feedback system. ev For the speed term prediction coefficient, K is the speed of motion input to the drive shaft. ea For the acceleration term prediction coefficient, This is the motion acceleration input to the drive shaft.

[0166] Optionally, in one embodiment of this application, after determining the source of tracking error, the method further includes: generating a dynamic precision control strategy that combines dynamic feedforward and dynamic tracking error pre-compensation method based on the source of tracking error, wherein the dynamic precision control strategy includes using a target dynamic feedforward control method to eliminate dynamic errors caused by robot dynamic characteristics and using a target dynamic tracking error pre-compensation method to compensate for dynamic tracking errors caused by the characteristics of the motor closed-loop feedback control system.

[0167] In some embodiments, this application can establish a dynamic precision control strategy that combines dynamic feedforward and dynamic tracking error pre-compensation method according to the source of tracking error. Dynamic feedforward is used to reduce or eliminate tracking error caused by nonlinear dynamic characteristics and nonlinear friction, and dynamic contour error pre-compensation method is used to reduce tracking error caused by closed-loop feedback control system characteristics.

[0168] The parallel robot dynamic contour error pre-compensation method proposed in this application can determine a rigid body dynamic model based on the dynamic parameters of the parallel machining robot, thereby calculating the theoretical driving force of each drive axis of the parallel machining robot and inputting it into the torque feedforward channel of the servo drive system for dynamic feedforward control. Using a pre-constructed tracking error prediction model of the parallel machining robot's drive axes, the dynamic contour error of the tool movement is predicted, and the motion trajectory is corrected within the task space to achieve high dynamic precision control of the parallel machining robot, effectively improving the robot's dynamic accuracy and machining quality. This solves the problem in related technologies where the mismatch between the controller performance and the nonlinear dynamic and nonlinear frictional characteristics of the controlled object (parallel machining robot) makes it difficult to guarantee the robot's dynamic accuracy and machining quality.

[0169] Next, referring to the accompanying drawings, a parallel robot dynamic contour error pre-compensation device according to an embodiment of this application is described.

[0170] Figure 10 This is a block diagram of a parallel robot dynamic contour error pre-compensation device according to an embodiment of this application.

[0171] like Figure 10 As shown, the parallel robot dynamic contour error pre-compensation device 10 includes: an acquisition module 100, a calculation module 200, and a prediction module 300.

[0172] Specifically, the acquisition module 100 is used to acquire the dynamic parameters of the parallel processing robot and determine the rigid body dynamic model of the parallel processing robot.

[0173] The calculation module 200 is used to calculate the theoretical driving force of each drive axis of the parallel processing robot based on the preset rigid body dynamics model, and input the theoretical driving force into the torque feedforward channel of the servo drive system for dynamic feedforward control.

[0174] The prediction module 300 is used to predict the dynamic contour error of the tool movement using a pre-built tracking error prediction model of the drive axis of the parallel machining robot, and correct the motion trajectory in the task space according to the dynamic contour error, so as to perform high dynamic precision control of the parallel machining robot.

[0175] Optionally, in one embodiment of this application, the apparatus 10 of this application embodiment further includes: an establishment module.

[0176] The module establishes a single-degree-of-freedom servo drive system based on multiple time-varying loads determined by the parallel machining robot before estimating the dynamic contour error of the tool movement. The single-degree-of-freedom servo drive system uses a proportional controller for the position loop, a proportional-integral controller for the velocity loop, and a proportional controller for the current loop. The controlled object is a motor rotor, which acts as a first-order inertial element. The time-varying loads caused by the mechanical body movement of the parallel machining robot act on the output of the current loop as disturbances to the control system. Velocity feedforward is added to the input of the velocity loop, and torque feedforward is added to the input of the current loop. Based on the single-degree-of-freedom servo drive control system, the dynamic error transfer function is derived as follows:

[0177] E(s)=E load (s)+E input (s)=G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)

[0178] Among them, E load (s) is the primary source, E input (s) is the second source, G eload (s) is the error transfer function from the first source, G einput (s) is the error transfer function from the second source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop, Q d (s) represents the motion command input to the drive shaft.

[0179] A tracking error prediction model for the drive axes of a parallel machining robot is established to identify the sources of tracking error. These sources include a first source caused by the dynamic characteristics of the parallel machining robot and a second source caused by the characteristics of the motor closed-loop feedback control system.

[0180] The primary source is:

[0181] E load (s)=G eload (s)(K t T ff (s)-T L (s))

[0182] Among them, G eload (s) is the error propagation function from the first source, K t T is the torque coefficient of the current loop. ff (s) represents the torque feedforward added to the control system, T L (s) represents the time-varying load acting at the output of the current loop.

[0183] The second source is:

[0184] E input (s)=G einput (s)Q d (s)

[0185] Among them, G einput (s) is the error transfer function from the second source, Q d (s) is the motion command input to the drive shaft.

[0186] Optionally, in one embodiment of this application, the apparatus 10 of this application embodiment further includes: a generation module.

[0187] The generation module is used to generate a dynamic precision control strategy that combines dynamic feedforward and dynamic tracking error pre-compensation methods after determining the source of tracking error. The dynamic precision control strategy includes using the target dynamic feedforward control method to eliminate dynamic errors caused by robot dynamic characteristics and using the target dynamic tracking error pre-compensation method to compensate for dynamic tracking errors caused by the characteristics of the motor closed-loop feedback control system.

[0188] Optionally, in one embodiment of this application, the tracking error prediction model is:

[0189]

[0190] in, K is the estimated value of the dynamic tracking error caused by the characteristics of the closed-loop feedback system. ev For the speed term prediction coefficient, K is the speed of motion input to the drive shaft. ea For the acceleration term prediction coefficient, This is the motion acceleration input to the drive shaft.

[0191] Optionally, in one embodiment of this application, the estimation module 300 includes: a first acquisition unit, a conversion unit, and a second acquisition unit.

[0192] The first acquisition unit is used to acquire the instruction trajectory of the end-effector of the parallel processing robot.

[0193] The conversion unit is used to convert the reference motion trajectory of the robot end-effector into the reference motion trajectory of the drive axis, and obtain the predicted value of the tracking error of the drive axis according to the tracking error prediction model.

[0194] The second acquisition unit is used to estimate the actual motion trajectory of the tool. Based on the reference motion trajectory and the estimated actual motion trajectory of the tool, it obtains the dynamic contour error. The estimation of the actual motion trajectory and the acquisition of the dynamic contour error include solving for the contour error by finding contour error points along the curve path. This involves using a lookup table to search for the point on the desired trajectory that is closest to the actual position. Since the contour error point is within a small neighborhood of the smallest point, the parameterized spline curve is Taylor-expanded at the smallest point. The calculation formula for the contour error point along the curve path is as follows:

[0195]

[0196] Among them, P fi For the contour error point, P qi Let u be the point on the desired trajectory that is closest to the actual position, Δu be the spline parameter of the curve path, Δu be the differential of the spline parameter, and o be a higher-order infinitesimal term.

[0197] By using differentiation to find the spline parameters, the tangent direction of the spline curve at the contour error point is obtained as follows:

[0198] P' fi =P' qi (u)+P” qi (u)Δu

[0199] Equations are constructed based on geometric relationships to solve for the differential of the spline parameters at the foot of the perpendicular, where the geometric relationships are:

[0200] (P ai -P fi )·P' fi =0

[0201] The equation is:

[0202]

[0203] Then, solve the cubic equation in one variable to obtain the differential of the spline parameters, and calculate the coordinates of the contour error points and the spline parameters, where the spline parameters are:

[0204] u f =u+Δu

[0205] The dynamic profile error is calculated as follows:

[0206] ε i =P fi -P ai

[0207] Where, ε i This refers to the contour error.

[0208] Optionally, in one embodiment of this application, the estimation module 300 includes: a third acquisition unit.

[0209] The third acquisition unit is used to perform contour error pre-compensation using the mirror method based on the dynamic contour error to obtain the corrected tool motion trajectory, thereby obtaining the corrected drive axis motion trajectory, and sending the corrected drive axis motion trajectory to the controller for execution. The corrected drive axis motion trajectory is as follows:

[0210] P ci =P ai +t i +ε i ,

[0211] Among them, P ci To determine the compensated tool tip position, P ai ε is the distance from the actual position on the desired trajectory. i The profile error of the tool motion, t i This represents the tracking error of the tool movement.

[0212] It should be noted that the foregoing explanation of the embodiment of the dynamic contour error pre-compensation method for parallel robots also applies to the dynamic contour error pre-compensation device for parallel robots in this embodiment, and will not be repeated here.

[0213] The parallel robot dynamic contour error pre-compensation device proposed in this application can determine a rigid body dynamic model based on the dynamic parameters of the parallel machining robot, thereby calculating the theoretical driving force of each drive axis of the parallel machining robot and inputting it into the torque feedforward channel of the servo drive system for dynamic feedforward control. Using a pre-constructed tracking error prediction model of the parallel machining robot's drive axes, the dynamic contour error of the tool movement is predicted, and the motion trajectory is corrected within the task space to achieve high dynamic precision control of the parallel machining robot, effectively improving the robot's dynamic accuracy and machining quality. This solves the problem in related technologies where the mismatch between the controller performance and the nonlinear dynamic and nonlinear frictional characteristics of the controlled object (parallel machining robot) makes it difficult to guarantee the robot's dynamic accuracy and machining quality.

[0214] Figure 11 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0215] The memory 1101, the processor 1102, and the computer program stored on the memory 1101 and executable on the processor 1102.

[0216] When the processor 1102 executes the program, it implements the parallel robot dynamic contour error pre-compensation method provided in the above embodiments.

[0217] Furthermore, electronic devices also include:

[0218] Communication interface 1103 is used for communication between memory 1101 and processor 1102.

[0219] The memory 1101 is used to store computer programs that can run on the processor 1102.

[0220] The memory 1101 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0221] If the memory 1101, processor 1102, and communication interface 1103 are implemented independently, then the communication interface 1103, memory 1101, and processor 1102 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 11 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0222] Optionally, in a specific implementation, if the memory 1101, processor 1102, and communication interface 1103 are integrated on a single chip, then the memory 1101, processor 1102, and communication interface 1103 can communicate with each other through an internal interface.

[0223] The processor 1102 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0224] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for pre-compensating dynamic contour errors of a parallel robot.

[0225] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0226] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0227] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0228] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0229] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0230] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0231] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0232] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A parallel robot dynamic contour error pre-compensation method, characterized in that, The method comprises the following steps: acquiring the dynamic parameters of the parallel robot, and determining a rigid body dynamics model of the parallel robot; based on the determined rigid body dynamics model, calculating theoretical driving forces of each driving shaft of the parallel robot, and inputting the theoretical driving forces into a torque feedforward channel of a single degree of freedom servo driving system for dynamics feedforward control; and using a pre-constructed tracking error estimation model of the driving shaft of the parallel robot, estimating a dynamic profile error of tool movement, and correcting a movement trajectory in a task space according to the dynamic profile error to control the parallel robot with high dynamic precision; the using a pre-constructed tracking error estimation model of the driving shaft of the parallel robot, estimating a dynamic profile error of tool movement, comprises: obtaining an instruction trajectory of a robot end tool of the parallel robot; converting the reference movement trajectory of the robot end tool into a reference movement trajectory of a driving shaft, and obtaining a tracking error prediction value of the driving shaft according to the tracking error estimation model; obtaining the dynamic profile error according to the reference movement trajectory and an actual movement trajectory reached by the tool according to a kinematics forward solution of the robot; wherein the obtaining the dynamic profile error according to the reference movement trajectory and the actual movement trajectory reached by the tool comprises solving the profile error by finding a curve path profile error point; wherein the solving the profile error by finding the curve path profile error point comprises searching for a point on an expected trajectory that is closest to an actual position by using a table lookup method, performing Taylor expansion on a parametric spline curve at the point to obtain a calculation formula of the curve path profile error point as follows: wherein, is the profile error point, is the point on the desired trajectory that is closest to the actual position, is the spline parameter of the curve path, is the spline parameter differential, is the higher order infinitesimal, obtaining a tangent direction of the spline curve at the profile error point by differentiating the spline parameter as follows: constructing an equation according to a geometric relationship to solve the differential of the spline parameter of the foot point, wherein the geometric relationship is as follows: wherein, is the point on the desired trajectory that is closest to the actual position, is the tangent direction of the spline curve at the contour error point, wherein the equation is as follows: solving a monomial cubic equation to obtain the differential of the spline parameter, and calculating the coordinates and the spline parameter of the profile error point, wherein the spline parameter of the profile error point is as follows: the solving the dynamic profile error is as follows: wherein is the profile error.

2. The parallel robot dynamic contour error pre-compensation method according to claim 1, characterized in that, before estimating the dynamic profile error of the tool movement, the method further comprises: determining a single degree of freedom servo driving system under a plurality of time-varying loads based on the parallel robot, wherein a position loop of the single degree of freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, a current loop adopts a proportional controller, a controlled object is a motor rotor, a time-varying load caused by a mechanical body movement of the parallel robot acts on an output end of the current loop as a disturbance of the control system, a speed feedforward is added to an input port of the speed loop, and a torque feedforward is added to an input port of the current loop; wherein a dynamic error transfer function is derived according to the single degree of freedom servo driving system as follows: wherein is a first source, is a second source, is an error transfer function of the first source, is an error transfer function of the second source, is a current loop torque coefficient, is a torque feed forward to the control system, is a time varying load acting on the current loop output, is a motion command input to the drive shaft; establishing a tracking error estimation model of the parallel robot driving shaft to determine tracking error sources, wherein the tracking error sources include a first source caused by dynamic characteristics of the parallel robot and a second source caused by characteristics of a motor closed-loop feedback control system; the first source is: the second source is: 。 3. The parallel robot dynamic contour error pre-compensation method according to claim 2, wherein, after determining the tracking error sources, further comprising: generating a dynamic accuracy control strategy combined with a target dynamic feedforward control method and a target dynamic tracking error pre-compensation method according to the tracking error sources, wherein the dynamic accuracy control strategy includes eliminating dynamic errors caused by dynamic characteristics of the robot by using the target dynamic feedforward control method and compensating for dynamic tracking errors caused by characteristics of the motor closed-loop feedback control system by using the target dynamic tracking error pre-compensation method.

4. The parallel robot dynamic contour error pre-compensation method according to claim 1, wherein, the tracking error estimation model is: wherein, is a dynamic tracking error estimate caused by closed loop feedback system characteristics, is a velocity term estimate coefficient, is a velocity of motion input to the drive shaft, is an acceleration term estimate coefficient, is an acceleration of motion input to the drive shaft, t is an interpolation time.

5. The parallel robot dynamic contour error pre-compensation method according to claim 1, wherein, correcting the motion trajectory in the task space according to the dynamic contour error, comprising: adopting a mirror method for contour error pre-compensation according to the dynamic contour error to obtain a corrected tool motion trajectory, so as to obtain a corrected driving shaft motion trajectory, and sending the corrected driving shaft motion trajectory to a controller for execution, wherein the corrected driving shaft motion trajectory is: ， wherein is the compensated tool tip position, is the profile error of the tool motion, is the tracking error of the tool motion.

6. A parallel robot dynamic contour error pre-compensation device, adapted to implement the method according to any one of claims 1-5, characterized in that, comprising: an acquisition module for acquiring dynamic parameters of the parallel robot and determining a rigid body dynamics model of the parallel robot; a calculation module for calculating theoretical driving forces of each driving shaft of the parallel robot based on the determined rigid body dynamics model, and inputting the theoretical driving forces to a torque feedforward channel of a single degree of freedom servo driving system for dynamic feedforward control; and an estimation module for estimating dynamic contour errors of tool motion by using a pre-constructed tracking error estimation model of the parallel robot driving shaft, and correcting the motion trajectory in the task space according to the dynamic contour errors to perform high dynamic accuracy control on the parallel robot.

7. The parallel robot dynamic contour error pre-compensation apparatus according to claim 6, wherein, further comprising: an establishment module for, before estimating the dynamic contour errors of the tool motion, determining a single degree of freedom servo driving system under a plurality of time-varying loads based on the parallel robot, wherein a position loop of the single degree of freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, and a current loop adopts a proportional controller, a controlled object is a motor rotor, as a first-order inertia element, a time-varying load caused by a mechanical body motion process of the parallel robot acts on an output end of the current loop, as a disturbance of the control system, a speed feedforward is added to an input port of the speed loop, and a torque feedforward is added to an input port of the current loop, wherein a dynamic error transfer function is derived according to the single degree of freedom servo driving system as: wherein is a first source, is a second source, is an error transfer function of the first source, is an error transfer function of the second source, is a current loop torque coefficient, is a torque feed forward to the control system, is a time varying load acting on the current loop output, is a motion command input to the drive shaft, establishing a tracking error estimation model of the parallel robot driving shaft to determine tracking error sources, wherein the tracking error sources include a first source caused by dynamic characteristics of the parallel robot and a second source caused by characteristics of a motor closed-loop feedback control system, the first source is: wherein is the error transfer function of the first source, is the torque coefficient of the current loop, is the torque feedforward added to the control system, is the time-varying load acting on the output of the current loop, the second source is: wherein, is the error transfer function of the second source, is the motion command input to the drive shaft.

8. An electronic device, comprising: comprising: - a memory, a processor and a computer program stored on the memory and runable on the processor, the processor executing the program to implement the parallel robot dynamic contour error pre-compensation method according to any one of claims 1-4.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor for implementing the parallel robot dynamic contour error pre-compensation method according to any one of claims 1-4.

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