Entropy-function-based motion planning method and system for welding device, and device and medium

Abstract

An entropy-function-based motion planning method for a welding device. The method comprises: by means of energy-consumption parameter indicators, constructing energy influence factors of a gantry shaft, a horizontal shaft and a robot body shaft; on the basis of the energy influence factors, constructing corresponding energy entropy functions; constructing an initial motion planning path; on the basis of the running process of the initial motion planning path, calculating a time entropy, and then in combination with a gantry-shaft energy entropy function, a horizontal-shaft energy entropy function and a robot-body energy entropy function, calculating a motion entropy of a single welding operation motion process; and for the calculated motion entropy, adjusting entropy influence factor coefficients of the gantry shaft, the horizontal shaft and the robot body shaft on the basis of a certain step size, and re-planning a motion planning path and calculating a motion entropy. The minimum energy consumption and the optimal operation during welding are achieved, and the high efficiency welding and the minimum energy consumption of welding by a device are achieved. Further provided are an entropy-function-based motion planning system for a welding device, and a computer device and a computer-readable storage medium.

Description

Motion planning method and system for welding equipment based on entropy function, equipment, and medium Technical Field

[0001] This invention relates to the field of shipbuilding technology, and in particular to a motion planning method, system, equipment, and medium for welding equipment based on entropy functions. Background Technology

[0002] In further promoting the automation and digital transformation of the manufacturing industry, robotic welding is currently a major technological direction in equipment manufacturing. Especially in the shipbuilding industry, the components to be welded are relatively large, and there are many weld seams distributed over a wide area. Therefore, welding tasks are mostly accomplished using a multi-axis motion combination of a large gantry, horizontal axis, and robot body axis. In the context of large gantry operation, energy consumption is a crucial consideration in the motion planning of welding equipment. While welding the same seam can sometimes be accomplished through individual robot movement or individual gantry axis movement—both methods—energy consumption is not comprehensively considered in these contexts.

[0003] Currently, motion planning for robotic welding based on multi-external-axis linkage, especially in cases with redundant solution sets, mainly relies on the subjective judgment of engineers. This involves planning the next level of motion equipment one by one, using methods such as keeping specific external axes stationary or moving within specific small intervals. This method is arbitrary, subjective, and lacks a scientific evaluation theoretical basis. Furthermore, for welding a series of welds, there are usually many possible motion planning paths, each capable of accomplishing the task. However, research on how to obtain a welding motion path that can both achieve the welding task and save energy is limited.

[0004] Therefore, there is an urgent need in the existing technology for a welding equipment motion planning method, system, equipment, and medium based on entropy function that can both achieve the welding operation task and reduce energy consumption. Summary of the Invention

[0005] The purpose of this invention is to provide a welding equipment motion planning method, system, equipment, and medium based on entropy function. By constructing an evaluation method based on comprehensive motion entropy of energy entropy and time entropy, a welding equipment motion planning method that automatically adjusts the energy influence factor of motion structure is designed to achieve multi-task energy-saving planning and control of welding equipment.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] A motion planning method for welding equipment based on entropy function includes the following steps:

[0008] By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0009] Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0010] Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0011] The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0012] For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0013] Furthermore, the step of constructing the energy influence factors of the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters includes:

[0014] The rated power of the motors and their servo drives for the gantry axis, horizontal axis, and robot body axis is used as an energy consumption parameter.

[0015] Obtain the rated power and normalize it to the 0-1 range;

[0016] Based on energy consumption parameters, the energy consumption of the gantry axis is determined to be > the energy consumption of the horizontal axis > the energy consumption of the robot body axis. Therefore, an energy influence factor K for the gantry axis is set. m Energy influence factor K of the horizontal axis h >Energy Influence Factor K of Robot Body Axis r .

[0017] Furthermore, the step of constructing the gantry shaft energy entropy function based on the energy influence factor of the gantry shaft includes:

[0018] Based on the energy influence factors, an energy entropy function for the gantry shaft of the moving parts of the welding equipment is constructed. The constructed gantry shaft energy entropy function E m for:

[0019] Where P m For the electrical control and drive power of the gantry shaft, V m V is the running speed of the gantry shaft. em L is the rated speed of the gantry shaft. m This refers to the running length of the gantry shaft.

[0020] Furthermore, the step of constructing the horizontal axis energy entropy function based on the horizontal axis energy influence factor includes:

[0021] Based on the energy influence factors, a horizontal axis energy entropy function E for the moving parts of the welding equipment is constructed. h for:

[0022] Where P h For the electrical control and drive power of the horizontal axis, V h V is the running speed of the horizontal axis. eh L is the rated speed of the horizontal axis. h This represents the running length of the horizontal axis.

[0023] Furthermore, the step of constructing the robot's body energy entropy function based on the energy influence factor of the horizontal axis includes:

[0024] Based on the energy influence factors, an energy entropy function for the robot body of the moving parts of the welding equipment is constructed, and the energy entropy function E of the robot body axis is constructed. r for:

[0025] Where the subscript i represents the i-th axis of the robot body, P ri V represents the electrical control and drive power of the i-th axis of the robot. ri Let V be the speed of the robot's i-th axis. eri Let A be the rated speed of the i-th axis of the robot. ri Let be the rotation angle of the i-th axis of the robot.

[0026] Furthermore, the step of constructing the initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements includes:

[0027] The robot is fixed above the starting point of the work path using a gantry axis and a horizontal axis. Based on the robot's end-effector pose required for the operation, the pose sequence U(P0P) from the starting point to the ending point is interpolated. N ), where P0 and P N Representing the 0th and Nth points of the interpolation, we plan the robot's motion path P0, P1...P from the starting point to the ending point. N ;

[0028] Record the motion processes of the gantry axis, horizontal axis, and robot body axis, and combine the energy entropy functions of the gantry axis, horizontal axis, and robot body to obtain the gantry axis energy entropy set E. mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N ), where P represents position, P0P N This represents the distance from the 0th point to the Nth point, i.e., from the starting point to the ending point.

[0029] According to the gantry shaft energy entropy set E mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N Find the minimum sum of the values ​​of the two numbers to obtain the robot's motion path from the starting point to the end point.

[0030] Furthermore, the step of calculating the time entropy based on the operation process of the initial motion planning path, and then combining the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation includes:

[0031] According to the gantry shaft energy entropy set E mU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. m (P0P N );

[0032] According to the horizontal axis energy entropy set E hU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. h (P0P N );

[0033] According to the robot's body axis energy entropy set E rU (P0P NCalculate the energy entropy E corresponding to the motion process from the starting point to the ending point. r (P0P N );

[0034] Construct the motion entropy of the running process, where the motion entropy E R Defined as: E R =H(E) E E T );

[0035] Where E E E represents energy entropy. T H represents the temporal entropy of motion, where H denotes the convolution operation between the energy entropy and the temporal entropy within the motion time T.

[0036] Time entropy E T Defined as:

[0037] Time entropy E T Converted to discrete form:

[0038] Motion entropy E R The formula for calculating E is: R =∑ JOB (K m ∑ U H(E m (P0P N ),E Tm )+K h ∑ U H(E h (P0P N ),E Th )+ K r ∑ U H(E r (P0P N ),E Tr ));

[0039] Where 'a' represents acceleration, 'JOB' indicates computation within the job set, and K... m K represents the energy influence factor of the gantry shaft. h K represents the energy influence factor of the horizontal axis. r The energy influence factor of the robot's body axis is represented by U, the motion set of the entire operation is represented by H, and P0P is represented by P0P. N E represents the distance from the 0th point to the Nth point. Tm E represents the time entropy of the gantry axis. Th E represents the time entropy of the horizontal axis. Tr This represents the temporal entropy of the robot's body axis.

[0040] Furthermore, the step of adjusting the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis with a certain step size based on the calculated motion entropy includes:

[0041] The calculated motion entropy is increased by a factor of K;

[0042] Set the positive or negative adjustment factor to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis.

[0043] Recalculate the motion entropy and determine whether the fluctuation of the motion entropy value has converged.

[0044] If convergence is achieved, probability calculations are performed, and the energy influence factors of the gantry axis, horizontal axis, and robot body axis are determined to be either positive or negative.

[0045] If the motion does not converge, determine whether the motion entropy decreases. If the motion entropy decreases, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are positive directional adjustment factors. If the motion entropy does not decrease, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are negative directional adjustment factors.

[0046] On the other hand, a motion planning system for welding equipment based on an entropy function is provided, the system comprising:

[0047] An energy influence factor module is constructed to construct energy influence factors for the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and their matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters.

[0048] An energy entropy function module is constructed to build the energy entropy function of the gantry axis based on the energy influence factor of the gantry axis, the energy entropy function of the horizontal axis based on the energy influence factor of the horizontal axis, and the energy entropy function of the robot body based on the energy influence factor of the horizontal axis.

[0049] The motion path planning module is used to construct an initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements. The initial motion planning path is to use the gantry axis and the horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0050] The motion entropy calculation module is used to calculate the time entropy based on the running process of the initial motion planning path, and then combine the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation process; for multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation;

[0051] The path adjustment module is used to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis in a certain step size based on the calculated motion entropy, replan the motion planning path and calculate the motion entropy. If the motion entropy decreases, the iterative adjustment continues in this way; otherwise, iterative adjustment is performed in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0052] In another aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0053] By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0054] Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0055] Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0056] The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0057] For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0058] In another aspect, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0059] By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0060] Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0061] Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0062] The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0063] For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0064] This application provides a motion planning method, system, equipment, and medium for welding equipment based on entropy functions. By constructing the gantry axis entropy function, the horizontal axis entropy function, and the robot body axis entropy function, the motion entropy value in the motion planning path is calculated in real time iteratively, and the energy influence factor of each axis is automatically adjusted to achieve a welding equipment motion planning method with low energy consumption and optimal path. This improves the comprehensive welding index of energy consumption and time consumption in the welding process, minimizes energy consumption and optimizes operation in the welding process, and achieves high-efficiency welding and minimum energy consumption of the equipment. Attached Figure Description

[0065] Figure 1 is a flowchart illustrating the motion planning method for welding equipment based on entropy function according to the present invention.

[0066] Figure 2 is a logic diagram of the welding equipment motion planning method based on entropy function of the present invention;

[0067] Figure 3 is a flowchart illustrating the steps of constructing the energy influence factors of the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters.

[0068] Figure 4 is a flowchart illustrating the steps of adjusting the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis with a certain step size based on the calculated motion entropy according to the present invention.

[0069] Figure 5 is a structural block diagram of a welding equipment motion planning system based on entropy function in one embodiment of this application;

[0070] Figure 6 is an internal structural diagram of a computer device in one embodiment of this application. Detailed Implementation

[0071] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0072] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component may be changed, and the layout of the components may also be more complex.

[0073] As shown in Figures 1 and 2, this application provides a motion planning method for welding equipment based on an entropy function, including the following steps:

[0074] Step S1) By using the rated power of the motors and matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0075] Step S2) Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0076] Step S3) Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use the gantry axis and the horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0077] Step S4) Calculate the time entropy based on the running process of the initial motion planning path, and then calculate the motion entropy of a single weld seam operation process by combining the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function; for multiple weld seams, interpolation is performed using the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam as stage points.

[0078] Step S5) Based on the calculated motion entropy, adjust the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis with a certain step size, replan the motion planning path and calculate the motion entropy. If the motion entropy decreases, continue to iterate and adjust in this way; otherwise, iterate and adjust in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0079] The planning method of the present invention includes the following steps in its specific implementation:

[0080] Step S1 includes: constructing an energy influence factor for each motion axis by using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters. Axis with higher rated power has a greater impact on motion energy. All rated power is normalized to the 0-1 range using a percentage method, such as the ratio of the gantry axis's rated power to the total power of all axes. This incorporates factors affecting motion energy consumption into the motion entropy. Considering the robot mounted on the horizontal axis and the horizontal axis mounted on the gantry axis, the energy consumption of the gantry axis > the energy consumption of the horizontal axis > the robot's energy consumption. Therefore, the energy influence factor K of the gantry axis is fundamentally determined. m Horizontal axis influence factor K h Robotics Impact Factor K r Considering the connection relationships and accessibility requirements of the robot's axes, the distinction between the influence factors of each axis will be weakened. Common industrial robots typically consist of six motion axes, denoted as R1 / R2 / R3 / R4 / R5 / R6, each driven by a motor. Therefore, the motor power of each axis is used as a reference for calculating its influence factor. Furthermore, considering the mechanical structure of the robot axes, the following approach is adopted: (Influence factors of robot axes R1 and R2) > (Influence factors of robot axes R3 / R4 / R5 / R6), meaning that robot axes R1 and R2 use the same influence factor K. r1 The robot's axes R3, R4, R5, and R6 all use the same influence factor K. r2 Meanwhile, the numerical difference between the two factors mentioned above is much smaller than the difference between the influence factors of the gantry axis and the horizontal axis.

[0081] As shown in Figure 3, the steps of constructing the energy influence factors of the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and their matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters include:

[0082] Step S11) The rated power of the motors and matching servo drives of the gantry axis, horizontal axis, and robot body axis is used as the energy consumption parameter.

[0083] Step S12) Obtain the rated power and normalize the rated power to the 0-1 range;

[0084] Step S13) Based on the energy consumption parameters, determine that the energy consumption of the gantry axis > the energy consumption of the horizontal axis > the energy consumption of the robot body axis, and set the energy influence factor K of the gantry axis. m Energy influence factor K of the horizontal axis h >Energy Influence Factor K of Robot Body Axis r .

[0085] The gantry axis entropy function, horizontal axis entropy function, and robot body axis entropy function constructed in step S2 comprehensively consider the energy consumption factors of the motion mechanism, including electrical control and drive power P, running speed V, rated speed Ve, running length L, and other factors.

[0086] In this embodiment, the step of constructing the gantry shaft energy entropy function based on the energy influence factor of the gantry shaft includes:

[0087] Based on the energy influence factors, an energy entropy function for the gantry shaft of the moving parts of the welding equipment is constructed. The constructed gantry shaft energy entropy function E m for:

[0088] Where P m For the electrical control and drive power of the gantry shaft, V m V is the running speed of the gantry shaft. em L is the rated speed of the gantry shaft. m This refers to the running length of the gantry shaft.

[0089] In this embodiment, the step of constructing the horizontal axis energy entropy function based on the horizontal axis energy influence factor includes:

[0090] Based on the energy influence factors, a horizontal axis energy entropy function E for the moving parts of the welding equipment is constructed. h for:

[0091] Where P h For the electrical control and drive power of the horizontal axis, V h V is the running speed of the horizontal axis. eh L is the rated speed of the horizontal axis. h This represents the running length of the horizontal axis.

[0092] In this embodiment, the step of constructing the robot's body energy entropy function based on the energy influence factor of the horizontal axis includes:

[0093] Based on the energy influence factors, an energy entropy function for the robot body of the moving parts of the welding equipment is constructed, and the energy entropy function E of the robot body axis is constructed. r for:

[0094] Where the subscript i represents the i-th axis of the robot body, P ri V represents the electrical control and drive power of the i-th axis of the robot. ri Let V be the speed of the robot's i-th axis. eri Let A be the rated speed of the i-th axis of the robot. ri Let be the rotation angle of the i-th axis of the robot.

[0095] In this embodiment, the step of constructing the initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements includes:

[0096] The robot is fixed above the starting point of the work path using a gantry axis and a horizontal axis. Based on the robot's end-effector pose required for the operation, the pose sequence U(P0P) from the starting point to the ending point is interpolated. N ), where P0 and P N Representing the 0th and Nth points of the interpolation, we plan the robot's motion path P0, P1...P from the starting point to the ending point. N ;

[0097] Record the motion processes of the gantry axis, horizontal axis, and robot body axis, and combine the energy entropy functions of the gantry axis, horizontal axis, and robot body to obtain the gantry axis energy entropy set E. mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N ), where P represents position, P0P N This represents the distance from the 0th point to the Nth point, i.e., from the starting point to the ending point.

[0098] According to the gantry shaft energy entropy set E mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N Find the minimum sum of the values ​​of the two numbers to obtain the robot's motion path from the starting point to the end point.

[0099] This process records the motion of each axis, including the gantry axis, the horizontal axis, and the robot's six body axes. These motion processes represent a series of energy entropies, forming a set of energy entropies, denoted as U. The set of energy entropies for the gantry axis is defined as: E. mU (P0P N The set of energy entropy along the horizontal axis is: E hU (P0P N The set of entropy values ​​for the body axis is: E rU (P0P N ), where P indicates the location, P0P N Let E represent the entire process from the 0th point (i.e., the starting point) to the Nth point (i.e., the ending point). mU (P0P N) represents the set of kinetic energy entropy of the gantry axes during the motion from the starting point to the end point. Similarly, the energy entropy of each axis during the entire motion from the starting point to the end point can be calculated in this way.

[0100] In this embodiment, the step of calculating the time entropy based on the operation process of the initial motion planning path, and then combining the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation includes:

[0101] According to the gantry shaft energy entropy set E mU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. m (P0P N );

[0102] According to the horizontal axis energy entropy set E hU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. h (P0P N );

[0103] According to the robot's body axis energy entropy set E rU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. r (P0P N );

[0104] Construct the motion entropy of the running process, where the motion entropy E R Defined as: E R =H(E) E E T );

[0105] Where E E E represents energy entropy. T H represents the temporal entropy of motion, where H denotes the convolution operation between the energy entropy and the temporal entropy within the motion time T.

[0106] Time entropy E T Defined as:

[0107] Time entropy E T Converted to discrete form:

[0108] Motion entropy E R The formula for calculation is:

[0109] Where a is acceleration, E R K represents motion entropy, JOB represents operations performed within the scope of the job set.m K represents the energy influence factor of the gantry shaft. h K represents the energy influence factor of the horizontal axis. r The energy influence factor of the robot's body axis is represented by U, the motion set of the entire operation is represented by H, and P0P is the convolution operator. N E represents the entire process from point 0 (the starting point) to point N (the ending point). Tr This represents the temporal entropy of the robot's body axis.

[0110] As shown in Figure 4, in this embodiment, the step of adjusting the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis with a certain step size based on the calculated motion entropy includes:

[0111] The calculated motion entropy is increased by a factor of K;

[0112] Set the positive or negative adjustment factor to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis.

[0113] Recalculate the motion entropy and determine whether the fluctuation of the motion entropy value has converged.

[0114] If convergence is achieved, probability calculations are performed, and the energy influence factors of the gantry axis, horizontal axis, and robot body axis are determined to be either positive or negative.

[0115] If the motion does not converge, determine whether the motion entropy decreases. If the motion entropy decreases, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are positive directional adjustment factors. If the motion entropy does not decrease, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are negative directional adjustment factors.

[0116] Step S5 includes: the constructed impact factor adjustment method is as follows:

[0117] For the situation where the robot end effector cannot reach the target area (i.e., the robot is unreachable) that occurs in steps S3 and S4, the motion entropy is set to a relatively large value. Considering a typical 3000W motor power and a running time of 60 seconds, this value can be set to be much larger than 3000*60, such as 9999999. For the motion entropy calculated under normal planning conditions in step S4, the entropy influence factor coefficient K of the gantry axis, horizontal axis, and robot body axis is finely adjusted with a certain step size. m K h K r For example, the initial impact factors that have been constructed can be fine-tuned using a step size of 0.01, such as 0.01*K. mThen, the motion planning and motion entropy are recalculated in this state. The rule for adjusting the direction is: if increasing the influence factor results in a decrease in motion entropy, the influence factor is iteratively adjusted by increasing the influence factor; otherwise, iterative adjustments are made by decreasing the influence factor. Furthermore, when entropy values ​​fluctuate and fail to converge, a specific probabilistic parameter is used to determine whether to increase or decrease the influence factor. This probability is determined based on the influence factor K. m K h K r The probability value is determined by the magnitude of the impact of the first C iterations on the entropy value. For example, if the entropy value decreases in A of the first C iterations, then the probability is determined according to... The probability is reduced by decreasing the influence factor, and the influence factor is adjusted in the above manner until the iteration reaches the specified maximum number of iterations or the entropy change ends within the specified tolerance range.

[0118] In one embodiment, as shown in Figure 5, a welding equipment motion planning system 10 based on an entropy function is provided, including: an energy influence factor construction module 1, an energy entropy function construction module 2, a motion path planning module 3, a motion entropy calculation module 4, and a path adjustment module 5.

[0119] The energy influence factor construction module 1 is used to construct energy influence factors for the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters.

[0120] The energy entropy function construction module 2 is used to construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0121] The motion path planning module 3 is used to construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements. The initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0122] The motion entropy calculation module 4 is used to calculate the time entropy based on the running process of the initial motion planning path, and then combine the gantry axis energy entropy function, the horizontal axis energy entropy function and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation process; for multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0123] The path adjustment module 5 is used to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis with a certain step size based on the calculated motion entropy, replan the motion planning path and calculate the motion entropy. If the motion entropy decreases, it continues to iterate and adjust in this way; otherwise, it iterates and adjusts in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0124] In this embodiment, the step of constructing the energy influence factors of the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and their corresponding servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters includes:

[0125] The rated power of the motors and their servo drives for the gantry axis, horizontal axis, and robot body axis is used as an energy consumption parameter.

[0126] Obtain the rated power and normalize it to the 0-1 range;

[0127] Based on energy consumption parameters, the energy consumption of the gantry axis is determined to be > the energy consumption of the horizontal axis > the energy consumption of the robot body axis. Therefore, an energy influence factor K for the gantry axis is set. m Energy influence factor K of the horizontal axis h >Energy Influence Factor K of Robot Body Axis r .

[0128] In this embodiment, the step of constructing the gantry shaft energy entropy function based on the energy influence factor of the gantry shaft includes:

[0129] Based on the energy influence factors, an energy entropy function for the gantry shaft of the moving parts of the welding equipment is constructed. The constructed gantry shaft energy entropy function E m for:

[0130] Where P m For the electrical control and drive power of the gantry shaft, V m V is the running speed of the gantry shaft. em L is the rated speed of the gantry shaft. m This refers to the running length of the gantry shaft.

[0131] In this embodiment, the step of constructing the horizontal axis energy entropy function based on the horizontal axis energy influence factor includes:

[0132] Based on the energy influence factors, a horizontal axis energy entropy function E for the moving parts of the welding equipment is constructed. h for:

[0133] Where P h For the electrical control and drive power of the horizontal axis, Vh V is the running speed of the horizontal axis. eh L is the rated speed of the horizontal axis. h This represents the running length of the horizontal axis.

[0134] In this embodiment, the step of constructing the robot's body energy entropy function based on the energy influence factor of the horizontal axis includes:

[0135] Based on the energy influence factors, an energy entropy function for the robot body of the moving parts of the welding equipment is constructed, and the energy entropy function E of the robot body axis is constructed. r for:

[0136] Where the subscript i represents the i-th axis of the robot body, P ri V represents the electrical control and drive power of the i-th axis of the robot. ri Let V be the speed of the robot's i-th axis. eri Let A be the rated speed of the i-th axis of the robot. ri Let be the rotation angle of the i-th axis of the robot.

[0137] In this embodiment, the step of constructing the initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements includes:

[0138] The robot is fixed above the starting point of the work path using a gantry axis and a horizontal axis. Based on the robot's end-effector pose required for the operation, the pose sequence U(P0P) from the starting point to the ending point is interpolated. N ), where P0 and P N Representing the 0th and Nth points of the interpolation, we plan the robot's motion path P0, P1...P from the starting point to the ending point. N ;

[0139] Record the motion processes of the gantry axis, horizontal axis, and robot body axis, and combine the energy entropy functions of the gantry axis, horizontal axis, and robot body to obtain the gantry axis energy entropy set E. mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N ), where P represents position, P0P N This represents the distance from the 0th point to the Nth point, i.e., from the starting point to the ending point.

[0140] According to the gantry shaft energy entropy set E mU (P0P N ), Horizontal axis energy entropy set E hU (P0PN ), Robot body axis energy entropy set E rU (P0P N Find the minimum sum of the values ​​of the two numbers to obtain the robot's motion path from the starting point to the end point.

[0141] In this embodiment, the step of calculating the time entropy based on the operation process of the initial motion planning path, and then combining the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation includes:

[0142] According to the gantry shaft energy entropy set E mU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. m (P0P N );

[0143] According to the horizontal axis energy entropy set E hU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. h (P0P N );

[0144] According to the robot's body axis energy entropy set E rU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. r (P0P N );

[0145] Construct the motion entropy of the running process, where the motion entropy E R Defined as: E R =H(E) E E T );

[0146] Where E E E represents energy entropy. T H represents the temporal entropy of motion, where H denotes the convolution operation between the energy entropy and the temporal entropy within the motion time T.

[0147] Time entropy E T Defined as:

[0148] Time entropy E T Converted to discrete form:

[0149] Motion entropy E R The formula for calculation is:

[0150] Where 'a' represents acceleration, 'JOB' indicates computation within the job set, and K...m K represents the energy influence factor of the gantry shaft. h K represents the energy influence factor of the horizontal axis. r The energy influence factor of the robot's body axis is represented by U, the motion set of the entire operation is represented by H, and P0P is represented by P0P. N E represents the distance from the 0th point to the Nth point. Tm E represents the time entropy of the gantry axis. Th E represents the time entropy of the horizontal axis. Tr This represents the temporal entropy of the robot's body axis.

[0151] In this embodiment, the step of adjusting the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis with a certain step size based on the calculated motion entropy includes:

[0152] The calculated motion entropy is increased by a factor of K;

[0153] Set the positive or negative adjustment factor to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis.

[0154] Recalculate the motion entropy and determine whether the fluctuation of the motion entropy value has converged.

[0155] If convergence is achieved, probability calculations are performed, and the energy influence factors of the gantry axis, horizontal axis, and robot body axis are determined to be either positive or negative.

[0156] If the motion does not converge, determine whether the motion entropy decreases. If the motion entropy decreases, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are positive directional adjustment factors. If the motion entropy does not decrease, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are negative directional adjustment factors.

[0157] The technical effects of the above-mentioned welding equipment motion planning system based on entropy function.

[0158] Specific limitations regarding the entropy function-based welding equipment motion planning system can be found in the above section on the limitations of the entropy function-based welding equipment motion planning method, and will not be repeated here. Each module in the aforementioned entropy function-based welding equipment motion planning system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0159] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram is shown in Figure 6. The computer device includes a processor, memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores welding equipment motion planning data based on an entropy function. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a welding equipment motion planning method based on an entropy function.

[0160] Those skilled in the art will understand that the structure shown in Figure 6 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0161] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0162] By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0163] Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0164] Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0165] The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0166] For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0167] For specific limitations on the steps implemented by the processor when executing a computer program, please refer to the limitations on the method of motion planning for welding equipment based on entropy function mentioned above, which will not be repeated here.

[0168] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0169] By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed.

[0170] Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis.

[0171] Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point.

[0172] The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation.

[0173] For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

[0174] For specific limitations on the implementation steps when a computer program is executed by a processor, please refer to the limitations on the method of motion planning for welding equipment based on entropy functions mentioned above, which will not be repeated here.

[0175] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A motion planning method for welding equipment based on entropy function, characterized in that, Includes the following steps: By using the rated power of the motors and their servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters, an energy influence factor for the gantry axis, horizontal axis, and robot body axis is constructed. Construct the gantry axis energy entropy function based on the energy influence factor of the gantry axis, construct the horizontal axis energy entropy function based on the energy influence factor of the horizontal axis, and construct the robot body energy entropy function based on the energy influence factor of the horizontal axis. Construct an initial motion planning path for the external axis and the robot body axis based on the task and welding process requirements; the initial motion planning path is to use a gantry axis and a horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point. The time entropy is calculated based on the operation process of the initial motion planning path, and then the motion entropy of a single weld seam operation process is calculated by combining the energy entropy function of the gantry axis, the energy entropy function of the horizontal axis, and the energy entropy function of the robot body. For multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation. For the calculated motion entropy, the entropy influence factor coefficients of the gantry axis, horizontal axis and robot body axis are adjusted with a certain step size. The motion planning path is replanned and the motion entropy is recalculated. If the motion entropy decreases, the iterative adjustment is continued in this way. Otherwise, the iterative adjustment is carried out in the opposite direction until the number of iterations exceeds the maximum number of iterations.

2. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The steps of constructing energy influence factors for the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and their corresponding servo drives as energy consumption parameters include: The rated power of the motors and their servo drives for the gantry axis, horizontal axis, and robot body axis is used as an energy consumption parameter. Obtain the rated power and normalize it to the 0-1 range; Based on energy consumption parameters, the energy consumption of the gantry axis is determined to be > the energy consumption of the horizontal axis > the energy consumption of the robot body axis. Therefore, an energy influence factor K for the gantry axis is set. m Energy influence factor K of the horizontal axis h >Energy Influence Factor K of Robot Body Axis r .

3. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The step of constructing the gantry shaft energy entropy function based on the energy influence factor of the gantry shaft includes: Based on the energy influence factors, an energy entropy function for the gantry shaft of the moving parts of the welding equipment is constructed. The constructed gantry shaft energy entropy function E m for: Where P m For the electrical control and drive power of the gantry shaft, V m V is the running speed of the gantry shaft. em L is the rated speed of the gantry shaft. m This refers to the running length of the gantry shaft.

4. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The steps for constructing the horizontal axis energy entropy function based on the horizontal axis energy influence factor include: Based on the energy influence factors, a horizontal axis energy entropy function E for the moving parts of the welding equipment is constructed. h for: Where P h For the electrical control and drive power of the horizontal axis, V h V is the running speed of the horizontal axis. eh L is the rated speed of the horizontal axis. h This represents the running length of the horizontal axis.

5. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The step of constructing the robot's body energy entropy function based on the energy influence factor of the horizontal axis includes: Based on the energy influence factors, an energy entropy function for the robot body of the moving parts of the welding equipment is constructed, and the energy entropy function E of the robot body axis is constructed. r for: Where the subscript i represents the i-th axis of the robot body, P ri V represents the electrical control and drive power of the i-th axis of the robot. ri Let V be the speed of the robot's i-th axis. eri Let A be the rated speed of the i-th axis of the robot. ri Let be the rotation angle of the i-th axis of the robot.

6. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The steps for constructing the initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements include: The robot is fixed above the starting point of the work path using a gantry axis and a horizontal axis. Based on the robot's end-effector pose required for the operation, the pose sequence U(P0P) from the starting point to the ending point is interpolated. N ), where P0 and P N Representing the 0th and Nth points of the interpolation, we plan the robot's motion path P0, P1...P from the starting point to the ending point. N ; Record the motion processes of the gantry axis, horizontal axis, and robot body axis, and combine the energy entropy functions of the gantry axis, horizontal axis, and robot body to obtain the gantry axis energy entropy set E. mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N ), where P represents position, P0P N This represents the distance from the 0th point to the Nth point, i.e., from the starting point to the ending point. According to the gantry shaft energy entropy set E mU (P0P N ), Horizontal axis energy entropy set E hU (P0P N ), Robot body axis energy entropy set E rU (P0P N Find the minimum sum of the values ​​of the two numbers to obtain the robot's motion path from the starting point to the end point.

7. The motion planning method for welding equipment based on entropy function according to claim 6, characterized in that, The step of calculating the time entropy based on the operation process of the initial motion planning path, and then combining the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation includes: According to the gantry shaft energy entropy set E mU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. m (P0P N ); According to the horizontal axis energy entropy set E hU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. h (P0P N ); According to the robot's body axis energy entropy set E rU (P0P N Calculate the energy entropy E corresponding to the motion process from the starting point to the ending point. r (P0P N ); Construct the motion entropy of the running process, where the motion entropy E R Defined as: E R =H(E) E E T ); Where E E E represents energy entropy. T H represents the temporal entropy of motion, where H denotes the convolution operation between the energy entropy and the temporal entropy within the motion time T. Time entropy E T Defined as: Time entropy E T Converted to discrete form: Motion entropy E R The formula for calculation is: HAVE BEEN R =∑ JOB (K m ∑ U H(E m (P0P N ),HAVE BEEN Tm )+K h ∑ U H(E h (P0P N ),HAVE BEEN Th )+ K r ∑ U H(E r (P0P N ),HAVE BEEN Tr )); Where 'a' represents acceleration, 'JOB' indicates computation within the job set, and K... m K represents the energy influence factor of the gantry shaft. h K represents the energy influence factor of the horizontal axis. r The energy influence factor of the robot's body axis is represented by U, the motion set of the entire operation is represented by H, and P0P is represented by P0P. N E represents the distance from the 0th point to the Nth point. Tm E represents the time entropy of the gantry axis. Th E represents the time entropy of the horizontal axis. Tr This represents the temporal entropy of the robot's body axis.

8. The motion planning method for welding equipment based on entropy function according to claim 1, characterized in that, The step of adjusting the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis with a certain step size based on the calculated motion entropy includes: The calculated motion entropy is increased by a factor of K; Set the positive or negative adjustment factor to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis. Recalculate the motion entropy and determine whether the fluctuation of the motion entropy value has converged. If convergence is achieved, probability calculations are performed, and the energy influence factors of the gantry axis, horizontal axis, and robot body axis are determined to be either positive or negative. If the motion does not converge, determine whether the motion entropy decreases. If the motion entropy decreases, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are positive directional adjustment factors. If the motion entropy does not decrease, determine that the energy influence factors of the gantry axis, horizontal axis, and robot body axis are negative directional adjustment factors.

9. A motion planning system for welding equipment based on entropy functions, characterized in that, The system includes: An energy influence factor module is constructed to construct energy influence factors for the gantry axis, horizontal axis, and robot body axis by using the rated power of the motors and their matching servo drives of the gantry axis, horizontal axis, and robot body axis as energy consumption parameters. An energy entropy function module is constructed to build the energy entropy function of the gantry axis based on the energy influence factor of the gantry axis, the energy entropy function of the horizontal axis based on the energy influence factor of the horizontal axis, and the energy entropy function of the robot body based on the energy influence factor of the horizontal axis. The motion path planning module is used to construct an initial motion planning path between the external axis and the robot body axis based on the task and welding process requirements. The initial motion planning path is to use the gantry axis and the horizontal axis fixed above the starting point of the work route, and interpolate the pose sequence from the starting point to the ending point of the work according to the robot end pose required by the task, and plan the motion path of the robot from the starting point to the ending point. The motion entropy calculation module is used to calculate the time entropy based on the running process of the initial motion planning path, and then combine the gantry axis energy entropy function, the horizontal axis energy entropy function, and the robot body energy entropy function to calculate the motion entropy of a single weld seam operation process; for multiple weld seams, the end pose of the previous weld seam, the end safety point of the previous weld seam, the start safety point of the next weld seam, and the start pose of the next weld seam are used as stage points for interpolation; The path adjustment module is used to adjust the entropy influence factor coefficients of the gantry axis, horizontal axis, and robot body axis in a certain step size based on the calculated motion entropy, replan the motion planning path and calculate the motion entropy. If the motion entropy decreases, the iterative adjustment continues in this way; otherwise, iterative adjustment is performed in the opposite direction until the number of iterations exceeds the maximum number of iterations.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

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