Mechanical arm machining tool path planning method and system based on filter

Abstract

The invention discloses a mechanical arm machining tool path planning method and system based on a filter, and relates to the technical field of mechanical arm tool machining. A motion path is obtained based on a numerical control file, and the overlapping time at the corner of the motion path is calculated based on the fairing error of a tool and a tool nose; calculating a delay time constant through a difference value between adjacent path points in the motion path, motion constraints of the cutter and the cutter tip and overlapping time, synchronizing motion of the cutter and the cutter tip, designing a filter by using the delay time constant, calculating a motion curve through the filter, and adjusting an original motion curve; establishing a delay time constant and a joint motion constraint equation based on the joint space and the cutter motion space, adding a joint space constraint to update the delay time constant, and obtaining a motion constraint through mechanical arm dynamics; and updating the motion path based on the interpolation equation. According to the method, the motion influence of robot dynamics on tail end cutter machining is considered, and a continuous and smooth cutter path can be rapidly generated.

Description

Technical Field

[0001] The present invention relates to the technical field of robot arm tool processing, and more particularly to a robot arm tool path planning method and system based on a filter. Background Art

[0002] With the rapid development of robot technology, industrial robots are playing an increasingly important role in the field of CNC machining. Compared with CNC machine tools, robotic arms as multi-axis machining equipment have the characteristics of large working space, strong environmental adaptability, and higher flexibility in production processes such as milling, grinding, polishing, and welding. However, due to their weak rigidity, industrial robots have higher requirements for trajectory planning of machining paths in machining tasks.

[0003] In the processing task, the discrete tool trajectory G01 is generated by the CAM software. Compared with CNC machine tools, industrial robots have more complex nonlinear kinematic transformations when executing linear commands. The weak continuity of the motion trajectory will lead to unstable robot joint speed, causing impact and causing violent vibration. Therefore, there are more important requirements for the smoothing and interpolation of the tool trajectory.

[0004] At present, the commonly used trajectory interpolation method considers using high-order continuous curves to fit or approximate the discrete G01 trajectory to generate a more continuous and smooth linear path, such as polynomial curves and spline curves. Depending on the requirements, consider fitting or approximating high-order curves in the global or local range of the trajectory. Then plan the tool's movement speed and acceleration and generate the tool's interpolation points based on the interpolation cycle. This method is divided into two steps: parameter curve fitting and tool speed planning. The calculation is time-consuming and does not consider the constraints of the robot's joint movements. It is easy to cause the robot joints to exceed the rated power of the motor during the movement process, causing vibration and reducing the processing quality.

[0005] Therefore, how to quickly generate a continuous and smooth tool trajectory is an urgent problem that technicians in this field need to solve. Summary of the invention

[0006] In view of this, the present invention provides a filter-based robot arm machining tool path planning method and system, which takes into account the influence of robot dynamics on the motion of end tool machining, so as to solve the problems existing in the background technology.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: A filter-based robot arm machining tool path planning method, comprising: The motion path is obtained through the NC file, and the overlap time at the corner of the motion path is calculated based on the smoothing error between the tool and the tool tip; The delay time constant is calculated by the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space and the overlap time, the original delay time constant is adjusted and the motion of the tool and the tool tip is synchronized, a filter corresponding to the tool and the tool tip is designed by using the adjusted delay time constant, a motion curve is calculated by using the filter, and the original motion curve is adjusted; An equation of a delay time constant and a joint motion constraint is established based on the relationship between the joint space and the tool motion space, the joint space constraint is added to update the delay time constant, and then the motion constraint of the joint space of the robot arm is obtained through the robot arm dynamics; The motion path is updated based on a preset interpolation equation in combination with the updated delay time constant and the motion constraint.

[0008] Preferably, the calculating the overlapping time at the corner of the motion path specifically includes: ; ; ; ; in, and Represent the overlap time constant of the tool and tool tip, and Represent the delay time constants of the tool and tool tip, respectively. , and Respectively represent the smoothing error of the tool and tool tip, and represents the velocity of adjacent line segments, and represents the position vector of the tool, , and represents the direction vector of the tool, and are the angles between the positions and directions of adjacent line segments respectively.

[0009] Preferably, the calculation of the delay time constant specifically includes: ; in, , is the delay time constant of the tool, , is the delay time constant of the tool tip, ; The coordinates of the path points adjacent to the tool position and The difference between The coordinates of the path points adjacent to the tool tip and The angle between are the tangential velocity, acceleration, jerk and acceleration constraints of the tool position, are the tangential angular velocity, angular acceleration, angular jerk and angular jerk constraints in the direction of the tool tip. The jerk is the first-order derivative of the acceleration with respect to time. is the first derivative of acceleration with respect to time.

[0010] Preferably, the calculating the motion curve through the filter specifically includes: ; Among them, the original speed signal The speed signal is obtained by convolution calculation of the pulse signal in the time domain and the FIR filter. , pulse signal It is obtained by Laplace transform of FIR filter transfer function.

[0011] Preferably, the equations for establishing the delay time constant and the joint motion constraint based on the relationship between the joint space and the tool motion space specifically include: extracting the code in the numerical control file, obtaining parameter information, converting the motion path into the robot end posture information through the rotation matrix, and then obtaining the joint angle information through the inverse solution, and performing torque constraints on the joint angle information through the dynamic model to obtain the joint motion constraint.

[0012] Preferably, obtaining the joint angle information by inverse solution specifically includes: ; ; in, is the robot rotation matrix, , and Represents the rotation angle of the end coordinate system around the axis, Represents the end position information of the robot, , and Represents the tip angle information.

[0013] Preferably, obtaining the motion constraint of the joint specifically includes: ; ; ; in, , and They are joint velocity, acceleration and jerk respectively, M represents the inertia tensor matrix in joint space, C represents the centrifugal force and Coriolis force matrix, G represents the gravity term matrix, represents the joint torque, is the friction torque, Represents the moment under the influence of environmental forces.

[0014] Preferably, the updating motion path specifically includes: ; Among them, the original location information The position information is obtained by performing four convolution calculations on the pulse signal in the time domain and the FIR filter. , It is a pulse signal.

[0015] A filter-based robot arm machining tool path planning system, comprising: The overlap time calculation module obtains the motion path based on the NC file and calculates the overlap time at the corner of the motion path based on the smoothing error between the tool and the tool tip; A filter construction module calculates a delay time constant through the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space and the overlap time, obtains a filter corresponding to the tool and the tool tip by using the delay time constant, and calculates a motion curve through the filter; A motion constraint module, which establishes a relationship between the joint space and the motion space based on the motion curve, adds joint space constraints to update the delay time constant, and then obtains the motion constraints of the joint space of the manipulator through the dynamics of the manipulator; The path updating module updates the motion path based on a preset interpolation equation in combination with an updated delay time constant and the motion constraint.

[0016] It can be seen from the above technical solution that, compared with the prior art, the present invention discloses a filter-based robotic arm machining tool path planning method and system, which completes the trajectory interpolation and speed planning of the industrial robot machining tool path, reduces the load of machining calculations, and improves the calculation speed; based on the robot dynamics, motion constraints are performed on different small segments of the path, which reduces the machining time and improves the machining efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0018] Figure 1 A diagram of the method steps provided by the present invention; Figure 2 A flow chart of robot tool path planning based on a high-order symmetrical FIR filter provided by the present invention; Figure 3 A schematic diagram of motion comparison after convolution of a high-order FIR filter and a second-order FIR filter provided by the present invention; Figure 4 A schematic diagram showing the comparison between the predicted torque and the actual torque after dynamic identification provided by the present invention; Figure 5 A schematic diagram showing the comparison between the actual and predicted friction force after the friction force identification provided by the present invention; Figure 6 A schematic diagram comparing joint dynamics constraints and unconstrained joint dynamics provided by the present invention; Figure 7 A schematic diagram showing a comparison between the planning based on dynamic constraints provided by the present invention and the planning under general constraints using conservative values; Figure 8 A schematic diagram of the smoothing error constraints on the tool position and tool tip direction provided by the present invention; Fig. 9 A schematic diagram showing the comparison between the smooth trajectory and the initial trajectory of the tool position provided by the present invention; Fig.10 A schematic diagram showing a comparison between a smooth trajectory and an initial trajectory in the tool tip direction provided by the present invention; Fig.11 A schematic diagram of the tool position and speed constraints in the tool tip direction provided by the present invention; Fig.12 A flow chart for identifying a set of kinetic parameters provided by the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] The embodiment of the present invention discloses a filter-based robot arm machining tool path planning method, such as Figure 1 As shown, including: The motion path is obtained through the NC file, and the overlap time at the corner of the motion path is calculated based on the smoothing error between the tool and the tool tip; The delay time constant is calculated by the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space, and the overlap time, the original delay time constant is adjusted and the motion of the tool and the tool tip is synchronized, the filter corresponding to the tool and the tool tip is designed by using the adjusted delay time constant, the motion curve is calculated by the filter, and the original motion curve is adjusted; Based on the relationship between the joint space and the tool motion space, the equation of the delay time constant and the joint motion constraint is established, the joint space constraint is added to update the delay time constant, and then the motion constraint of the robot joint space is obtained through the robot dynamics; Based on the preset interpolation equation, the motion path is updated in combination with the updated delay time constant and the motion constraint.

[0021] like Figure 2 As shown, the specific process of this embodiment includes: converting the G01 code based on the tool path into the coordinates of the end posture of the robot arm, calculating the delay time constant of the filter by the motion constraint of the tool, and solving the motion of the robot arm joint space by using inverse kinematics for the coordinates of the end posture, and obtaining the joint motion constraint in each path segment by performing joint torque constraint on the identified dynamic model, and then updating the delay time constant according to the relationship between the joint motion and the tool motion; thus, the time constant satisfying the tool motion space and the joint motion space is obtained, and the constant is adjusted to satisfy the optimal motion time and the synchronous motion of the tool position and the tool tip direction; then the overlap time at the path corner is calculated to satisfy the required smoothing error, and the time constant of the two paths at the corner is adjusted according to the overlap time; finally, the filter delay time constant is substituted into the interpolation equation, and the interpolation point of the robot joint space is obtained by the interpolation cycle and inverse kinematics.

[0022] In a specific embodiment, the overlap time at the path corner is calculated to control the smoothing error of the tool. The smoothing error of the tool position is: ; in, and They represent the trajectory point n at the error midpoint and the corner respectively, is the distance from trajectory point n-1 to the midpoint of the error, is the distance from the error midpoint to trajectory point n+1, , are the direction vector from trajectory point to n and the direction vector from trajectory point n to n+1, represents the i-th delay time constant of the tool position, is the overlap time, and the calculation formula of the overlap time is obtained by transforming the above formula, where In solving the formula of The cubic equation of one variable, according to Sheng Jin's discriminant The solution with only one real root in the overlapping time can be obtained, which simplifies the calculation process: ; ; For the calculation of the smoothing error in the tool tip direction, the same calculation method as the tool position is used: ; ; in, and Represent the overlap time constant of the tool and tool tip, and Represent the delay time constants of the tool and tool tip, respectively. , and Respectively represent the smoothing error of the tool and tool tip, and represents the velocity of adjacent line segments, and represents the position vector of the tool, , and represents the direction vector of the tool, and are the angles between the positions and directions of adjacent line segments respectively.

[0023] In the process of calculating the smoothing error, the midpoint of the error with equal speeds before and after the corner is used as the calculation standard, ensuring that the calculated overlap time can meet the smoothing requirements under both unequal and equal speed conditions.

[0024] The high-order filter proposed in the present invention performs one more convolution calculation than the common second-order FIR filter. Figure 3 It can be seen that the motion curve obtained by the proposed third-order FIR filter convolution calculation is smoother, and the acceleration curve is continuous without step. The design steps of the tool position and tool tip direction filter include: In a specific embodiment, the difference between adjacent path points is The delay time constant of the high-order filter is calculated based on the constraints of the tool in the motion space, including: ; in, , is the delay time constant of the tool, , is the delay time constant of the tool tip, ; The coordinates of the path points adjacent to the tool position and The difference between The coordinates of the path points adjacent to the tool tip and The angle between are the tangential velocity, acceleration, jerk and acceleration constraints of the tool position, are the tangential angular velocity, angular acceleration, angular jerk and angular jerk constraints in the direction of the tool tip. The jerk is the first-order derivative of the acceleration with respect to time. is the first derivative of acceleration with respect to time.

[0025] In order to ensure the optimal time-based robot motion, the above inequality is converted into an equation. The FIR filter is designed based on the calculated delay time constant, and then convolved with the tool position and the velocity pulse in the tool tip direction to obtain a smoother motion curve: ; Among them, the original speed signal The speed signal is obtained by convolution calculation of the pulse signal in the time domain and the FIR filter. , pulse signal It is obtained by Laplace transform of FIR filter transfer function.

[0026] In a specific embodiment, an equation for a delay time constant and a joint motion constraint is established based on the relationship between the joint space and the tool motion space, specifically including: extracting the code in the numerical control file, obtaining parameter information, converting the motion path into the robot end posture information through a rotation matrix, and then obtaining the joint angle information through an inverse solution, obtaining the torque and motion relationship of the robot through dynamic modeling and identification, and obtaining the motion constraint of the robot joint space from the motion of the robot joint space combined with the motor performance analysis.

[0027] according to Figure 4 , Figure 5 and Fig.12 As shown, the process of identifying the kinetic parameter set of the present invention is as follows: The steps to constrain the motion of the robot arm according to joint space dynamics include: Step B1: Establish a dynamic model by recursively calculating the Newton-Euler equation, and then linearize the equation to obtain a dynamic equation that can be calculated: ; ; in is the observation matrix with motion information, is the minimum identifiable parameter set, which can be obtained by QR decomposition. C represents the centrifugal force and Coriolis force matrix, G represents the gravity matrix, represents the joint torque, is the friction torque, Represents the moment under the influence of environmental forces.

[0028] Step B2: Design the excitation trajectory and nonlinear friction model, and use the fifth-order Fourier series to form a periodic excitation trajectory: ; in, , is the amplitude of the sine and cosine functions at the i-th joint to be optimized, represents the fundamental frequency, is the constant term of the i-th joint position, represents the number of sine and cosine terms, , and Represents the joint motion to be optimized as a function of time.

[0029] Considering the constraints such as the initial and final motion information of the robot and the space limit of the joint, the condition number of the matrix with motion information is used as an indicator to optimize the excitation trajectory parameters: ; ; in, represents the condition number of the matrix with motion information, , and represents the position, velocity and acceleration of the i-th joint, and Represent the start time and end time of the excitation trajectory respectively.

[0030] The established friction model is transformed into a form with the multiplication of the linearized parameter matrix and the nonlinear parameter matrix, so that the matrix is ​​substituted into the parameter set and the observation matrix respectively: ; in, represents the Coulomb friction coefficient, represents the viscous friction coefficient, Represents the bias parameter of the friction force in the positive and negative directions of the robot movement, Represents the nonlinear coefficient.

[0031] Step B3: The motion information and current data collected during the excitation trajectory movement are used to identify the dynamic model of the robot using an iterative weighted least squares algorithm.

[0032] ; in, and Represent the moment residual and acquisition moment respectively, and are the observation matrix and the estimated values ​​of the parameter set obtained by the initial identification, and Represent the weights before and after the update, respectively. represents the normalized moment residual, Represents the weighting function used to update the weights. After the weights are obtained through initial identification, the weight formula is used to obtain a new parameter set: .

[0033] Step B4: Convert the tool path information into the end-of-arm posture information through the rotation matrix, and then obtain the robot's joint angle information through inverse solution.

[0034] ; in, According to the selected workspace, the relationship with the tool position information can be obtained through the tool tip vector With the robot rotation matrix The relationship of the Euler angles at the end of the robotic arm can be obtained: ; in, is the robot rotation matrix, , and Represents the rotation angle of the end coordinate system around the axis, Represents the end position information of the robot, , and Represents the tip angle information.

[0035] Through the above steps, the conversion relationship between the end posture information of the robot arm and the tool path information is obtained, and then the joint angle information is obtained through the inverse solution of the robot arm.

[0036] In a specific embodiment, referring to the conversion information between the tool path and the Cartesian space coordinates of the robot and the identified dynamic model of the robot, the joint space constraint step includes: Step B5: Convert the tool path into the space motion of the robot joint by step B4, and then perform torque constraint through the identified dynamic model to obtain the motion constraint of the joint, which specifically includes: ; ; ; in, , and They are the robot joint velocity, acceleration and jerk respectively, M represents the inertia tensor matrix in the joint space, C represents the centrifugal force and Coriolis force matrix, G represents the gravity term matrix, represents the joint torque, is the friction torque, Represents the torque under the influence of environmental forces, and the motion constraints of the joints are obtained through the constraint torque , and ,in The value can be obtained by differential acceleration.

[0037] Step B6: Establish the relationship between joint motion and tool motion: ; in , and Represent the velocity, acceleration and jerk of the robot’s ith joint, , , and Represent tool displacement, velocity, acceleration and jerk respectively, which can be obtained by , and Get the maximum speed, acceleration and jerk of the tool in this path. , and Respectively represent the first-order, second-order and third-order derivatives of the joint displacement of the robot's ith joint on the tool displacement. According to step B5, the joint motion is constrained: ; in, Represents the joint angular velocity, joint angular acceleration, and joint angular jerk constraints of this path segment obtained under the dynamic torque constraints.

[0038] The delay time constant under the tangential constraint By comparison, we can get the delay time constant under the joint space constraint. : ; After this step, the delay time constant is updated to meet the motion constraints of the robot under the joint space dynamics. The calculation method of the tool position is the same as the calculation result of the time constant in the tool tip direction: ; in, , and They represent the tool tip displacement, maximum tool tip angular velocity and maximum tool tip angular acceleration under the tool tip path, respectively. , and They represent the first-order, second-order, and third-order derivatives of the joint angular displacement of the robot at the i-th joint with respect to the tool tip angular displacement.

[0039] In a specific embodiment, after obtaining the updated filter delay time constant through the robot arm joint constraints, the interpolation step includes: The delay time constants of the tool position and tool tip direction should satisfy the optimal motion time and achieve the following relationship: ; When the tool position motion constraint does not meet the above conditions, the processing delay time constant needs to be updated. When , adjust the value of the acceleration to satisfy the inequality relationship: ; When not satisfied When , adjust the acceleration value to satisfy the inequality relationship: ; When not satisfied When , the value of the adjustment speed satisfies the inequality relationship: ; When not satisfied and When , adjust the values ​​of acceleration and jerk to satisfy the inequality relationship: ; When not satisfied , and When , adjust the values ​​of velocity, acceleration and jerk to satisfy the inequality relationship: ; After adjusting the delay time constants of the tool position and tool tip direction, the movement of the position and direction needs to be processed to achieve the effect of synchronous movement in time: ; Among them, the tool position movement time is The movement time of the tool tip direction is .

[0040] In a specific embodiment, the adjusted time constant is substituted into the interpolation equation, and then the interpolation instruction of the tool processing path is generated according to the interpolation cycle: ; Among them, the original location information The position information is obtained by performing four convolution calculations on the pulse signal in the time domain and the FIR filter. , It is a pulse signal.

[0041] The interpolation points formed after the spatial dynamics constraints of the robot joints are compared with the interpolation points formed under the conservative value constraints of the robot joint motion. Figure 7 It can be found that the motion constraints obtained after dynamic identification reduce the tool movement time and improve the efficiency of tool processing motion; the smoothing error and smoothing trajectory obtained by the method are as follows Figure 8 , Fig. 9 , Fig.10 As shown in the figure, it can be seen that after adopting the invention, the smoothing error constraints of the tool position and the tool tip direction are kept within the range of 0.04mm and 0.004mm respectively. Fig.11 It can be seen that after the inventive steps, the tool speed and tool tip angular velocity still meet the constraints.

[0042] A filter-based robot arm machining tool path planning system, comprising: The overlap time calculation module obtains the motion path based on the NC file and calculates the overlap time at the corner of the motion path based on the smoothing error between the tool and the tool tip; The filter construction module calculates the delay time constant through the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space, and the overlap time, obtains the filter corresponding to the tool and the tool tip by using the delay time constant, and calculates the motion curve through the filter; The motion constraint module establishes the relationship between the joint space and the motion space based on the motion curve, adds the joint space constraint to update the delay time constant, and then obtains the motion constraint of the manipulator joint space through the manipulator dynamics; The path update module updates the motion path based on a preset interpolation equation combined with an updated delay time constant and motion constraints.

[0043] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0044] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A filter-based robot arm machining tool path planning method, characterized in that: include: The motion path is obtained through the NC file, and the overlap time at the corner of the motion path is calculated based on the smoothing error between the tool and the tool tip; The delay time constant is calculated by the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space and the overlap time, the original delay time constant is adjusted and the motion of the tool and the tool tip is synchronized, a filter corresponding to the tool and the tool tip is designed by using the adjusted delay time constant, a motion curve is calculated by using the filter, and the original motion curve is adjusted; An equation of a delay time constant and a joint motion constraint is established based on the relationship between the joint space and the tool motion space, the joint space constraint is added to update the delay time constant, and then the motion constraint of the joint space of the robot arm is obtained through the robot arm dynamics; The motion path is updated based on a preset interpolation equation in combination with the updated delay time constant and the motion constraint.

2. A filter-based robot arm machining tool path planning method according to claim 1, characterized in that: The calculation of the overlapping time at the corner of the motion path specifically includes: ； ； ； ； in, and Represent the overlap time constant of the tool and tool tip, and Represent the delay time constants of the tool and tool tip, respectively. , and Respectively represent the smoothing error of the tool and tool tip, and represents the velocity of adjacent line segments, and represents the position vector of the tool, , and represents the direction vector of the tool, and are the angles between the positions and directions of adjacent line segments respectively.

3. A filter-based robot arm machining tool path planning method according to claim 2, characterized in that: The calculation of the delay time constant specifically includes: ； in, , is the delay time constant of the tool, , is the delay time constant of the tool tip, ; The coordinates of the path points adjacent to the tool position and The difference between The coordinates of the path points adjacent to the tool tip and The angle between are the tangential velocity, acceleration, jerk and acceleration constraints of the tool position, are the tangential angular velocity, angular acceleration, angular jerk and angular jerk constraints in the direction of the tool tip. The jerk is the first-order derivative of the acceleration with respect to time. is the first derivative of acceleration with respect to time.

4. The filter-based robot arm machining tool path planning method according to claim 2, characterized in that: The calculating of the motion curve by the filter specifically comprises: ； Among them, the original speed signal The speed signal is obtained by convolution calculation of the pulse signal in the time domain and the FIR filter. , pulse signal It is obtained by Laplace transform of FIR filter transfer function.

5. The filter-based robot arm machining tool path planning method according to claim 2, characterized in that: The equations for establishing the delay time constant and the joint motion constraint based on the relationship between the joint space and the tool motion space specifically include: extracting the code in the numerical control file, obtaining parameter information, converting the motion path into the robot end posture information through the rotation matrix, and then obtaining the joint angle information through the inverse solution, and applying torque constraints to the joint angle information through the dynamic model to obtain the joint motion constraint.

6. The filter-based robot arm machining tool path planning method according to claim 5, characterized in that: The obtaining of the joint angle information by inverse solution specifically includes: ； ； in, is the robot rotation matrix, , and Represents the rotation angle of the end coordinate system around the axis, Represents the robot's end position information, , and Represents the tip angle information.

7. A filter-based robot arm machining tool path planning method according to claim 6, characterized in that: The motion constraints of the joints obtained specifically include: ； ； ； in, , and They are joint velocity, acceleration and jerk respectively, M represents the inertia tensor matrix in joint space, C represents the centrifugal force and Coriolis force matrix, G represents the gravity term matrix, represents the joint torque, is the friction torque, Represents the moment under the influence of environmental forces.

8. The filter-based robot arm machining tool path planning method according to claim 6, characterized in that: The updating motion path specifically includes: ； Among them, the original location information The position information is obtained by performing four convolution calculations on the pulse signal in the time domain and the FIR filter. , It is a pulse signal.

9. A filter-based robot arm machining tool path planning system, using a filter-based robot arm machining tool path planning method according to any one of claims 1 to 8, characterized in that: include: The overlap time calculation module obtains the motion path based on the NC file and calculates the overlap time at the corner of the motion path based on the smoothing error between the tool and the tool tip; A filter construction module calculates a delay time constant through the difference between adjacent path points in the motion path, the constraint between the tool and the tool tip in the motion space and the overlap time, obtains a filter corresponding to the tool and the tool tip by using the delay time constant, and calculates a motion curve through the filter; A motion constraint module, which establishes a relationship between the joint space and the motion space based on the motion curve, adds joint space constraints to update the delay time constant, and then obtains the motion constraints of the joint space of the manipulator through the dynamics of the manipulator; The path updating module updates the motion path based on a preset interpolation equation in combination with an updated delay time constant and the motion constraint.

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