Process auxiliary planning system and method based on visual positioning

Abstract

The invention belongs to the field of intelligent processing, relates to a visual positioning technology, is used for solving the problem that a single logic control mode cannot meet different application environments of an industrial robot, and particularly relates to a process auxiliary planning system and method based on visual positioning. The auxiliary planning platform is in communication connection with a positioning analysis module, a path monitoring module, a path analysis module and a database; the positioning analysis module is used for performing positioning analysis on each target object in the industrial workshop; the industrial robot position information, the target station path information and the robot path information form a positioning information group, and the positioning information group is sent to the path monitoring module through the auxiliary planning platform; according to the invention, each target object in the industrial workshop can be positioned and analyzed, and the positioning information is obtained after the positioning image is processed by adopting an image processing technology, so that data support is provided for path monitoring analysis and path planning analysis through the positioning information.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent processing, relates to visual positioning technology, and specifically is a process auxiliary planning system and method based on visual positioning. Background Art

[0002] The process-assisted planning method based on visual positioning mainly involves using visual technology to identify and locate the target object, and optimize the operation path or work trajectory based on this information to improve operation accuracy and work efficiency.

[0003] The process-assisted planning system in the prior art can only plan the formal path of the industrial robot based on a single logic. However, for the complex operating environment in the industrial workshop and the changeable load state of the industrial robot, the single logic control method cannot meet the different application environments of the industrial robot, resulting in the low applicability of the existing process-assisted planning system.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a process-assisted planning system and method based on visual positioning, which is used to solve the problem that a single logic control method cannot meet the different application environments of industrial robots; The technical problem to be solved by the present invention is: how to provide a process-assisted planning system and method based on visual positioning that can optimize the planned path according to the complex operating environment in the industrial workshop and the changeable load state of the industrial robot.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A process auxiliary planning system and method based on visual positioning, comprising an auxiliary planning platform, wherein the auxiliary planning platform is communicatively connected with a positioning analysis module, a path monitoring module, a path analysis module and a database; The positioning analysis module is used to perform positioning analysis on each target object in the industrial workshop and obtain; the industrial robot position information, target station path information and robot path information constitute a positioning information group and send the positioning information group to the path monitoring module through the auxiliary planning platform; The path monitoring module is used to perform obstruction analysis on robot-specific channels in the industrial workshop: marking robot-specific channels in the robot path information as normal channels or obstruction channels, and deleting all obstruction channels from the positioning information; The path analysis module is used to plan and analyze the driving routes of industrial robots in industrial workshops: generate several driving routes according to the industrial robot position information, target workstation path information and updated robot path information in the positioning information, then mark the industrial robot as an analysis object, obtain the stability coefficient PW of the analysis object, determine whether the load stability of the analysis object meets the requirements through the stability coefficient PW, and generate an efficiency target route or a stability target route.

[0007] Furthermore, the process of acquiring the industrial robot position information, target workstation path information and robot path information includes: taking a bird's-eye view image of the industrial workshop and marking the obtained image as a positioning image, enlarging the positioning image into a pixel grid image and performing a grayscale transformation, using a binary method to extract the edge information of the industrial robot and the target workstation in the positioning image and marking the positions of the industrial robot and the target workstation, and then extracting the robot path information in the positioning image. The robot path information includes a number of robot-specific channels, and the robot-specific channels are defined by two parallel marking coils.

[0008] Furthermore, the specific process of marking the robot-dedicated channel as a normal channel or an obstruction channel includes: retrieving the obstacle grayscale range through the database, marking the area between the two marking lines of the robot-dedicated channel as the monitoring area, and obtaining the obstruction coefficient ZA of the monitoring area; retrieving the obstruction threshold ZAmax through the database, and comparing the obstruction coefficient ZA of the monitoring area with the obstruction threshold ZAmax: if the obstruction coefficient ZA is less than the obstruction threshold ZAmax, the corresponding robot-dedicated channel is marked as a normal channel; if the obstruction coefficient ZA is greater than or equal to the obstruction threshold ZAmax, the corresponding robot-dedicated channel is marked as an obstruction channel.

[0009] Furthermore, the process of obtaining the obstruction coefficient ZA of the monitoring area includes: marking the pixel grids in the monitoring area whose grayscale values ​​are within the grayscale range of the obstacle as obstruction grids, forming an obstruction area by the obstruction grids that are in contact with each other, and obtaining the coverage data FG and the concentrated data JZ of the monitoring area, the coverage data FG is the total number of obstruction grids in the monitoring area, and the process of obtaining the concentrated data JZ includes: marking the number of obstruction grids in the obstruction area as the concentrated value of the obstruction area, and marking the maximum value of the concentrated values ​​in all obstruction areas as the concentrated data JZ; the obstruction coefficient ZA of the monitoring area is obtained by the formula ZA=k1*JZ+k2*FG, wherein k1 and k2 are both proportional coefficients, and k1>k2>1.

[0010] Furthermore, the process of obtaining the stability coefficient PW of the analysis object includes: obtaining the weight data FZ and space data KJ of the analysis object, the weight data FZ is the weight value of the load on the analysis object, and the space data KJ is the volume value of the load on the analysis object; the stability coefficient PW of the analysis object is obtained by the formula PW=m1*FZ+m2*KJ, wherein m1 and m2 are both proportional coefficients, and m1>m2>1.

[0011] Furthermore, the specific process of determining whether the load stability of the analysis object meets the requirements includes: retrieving the stability threshold PWmax through the database, and comparing the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, then it is determined that the load stability of the analysis object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, then it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, and the driving route with the smallest switching value is marked as the stability target route.

[0012] Furthermore, the path analysis module is also communicatively connected to the industrial robot control terminal and the optimization analysis module; After receiving the efficiency target route / stable target route, the industrial robot control terminal controls the industrial robot to move according to the efficiency target route / stable target route until the industrial robot reaches the target workstation; The optimization analysis module is used to optimize and analyze the route planning of the industrial robot: the difference between the time when the industrial robot arrives at the target workstation and the time when the industrial robot control terminal receives the efficiency target route / smooth target route is marked as the time difference value of this execution process, the straight-line distance between the industrial robot and the target workstation before moving is marked as the path value of the execution process, and the ratio of the path value to the time difference value is marked as the execution coefficient of the execution process; an optimization cycle is generated, and the execution coefficients of all execution processes that use the efficiency target route for robot movement control within the optimization cycle are summed and averaged to obtain the efficiency priority value, and the optimization cycle is optimized. The execution coefficients of all execution processes that use a smooth target route for robot movement control during the period are summed and averaged to obtain a smooth priority value, the difference between the efficiency priority value and the smooth priority value is marked as an optimization necessary value, and the optimization necessary value is compared with a preset optimization necessary threshold: if the optimization necessary value is less than the optimization necessary threshold, it is determined that the path planning mode of the industrial robot within the optimization period is not necessary for optimization; if the optimization necessary value is greater than or equal to the optimization necessary threshold, it is determined that the path planning mode of the industrial robot within the optimization period is necessary for optimization, and a balanced optimization signal is generated and sent to the path analysis module.

[0013] Furthermore, after receiving the balanced optimization signal, the path analysis module optimizes the path planning process of the analysis object in a specific process including: comparing the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, it is determined that the load stability of the analysis object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, the driving routes are arranged in order of driving distance from short to long to obtain an efficiency sequence, the driving routes are sorted in order of switching value from small to large to obtain a switching sequence, the sum of the serial numbers of the driving routes in the efficiency sequence and the switching sequence is marked as the balanced value, and the driving route with the smallest balanced value is marked as the balanced target route; the efficiency target route or the balanced target route is sent to the industrial robot control terminal.

[0014] The present invention has the following beneficial effects: 1. Through the positioning analysis module, each target object in the industrial workshop can be positioned and analyzed. According to the industrial workshop, images are taken and the positioning images are processed by image processing technology to obtain positioning information, thereby providing data support for path monitoring analysis and path planning analysis through positioning information; 2. The path detection module can be used to analyze the obstacles of the robot-dedicated channels in the industrial workshop. The obstacle coefficient can be obtained by comprehensive analysis and calculation based on multiple obstacle data in the monitoring area. The overall smoothness of the monitoring area can be fed back through the obstacle coefficient. The robot-dedicated channels in the positioning information can be updated according to the feedback results to avoid obstacles to the robot operation after the route is generated. 3. The path analysis module can plan and analyze the driving routes of industrial robots in industrial workshops and obtain the stability coefficient. The stability coefficient is used to evaluate the stability requirements of the analyzed object during operation, and then different methods are used to generate corresponding target routes based on the evaluation results. Targeted recommended routes are matched under different operating environments to improve the actual operating efficiency of industrial robots. 4. The optimization analysis module can be used to optimize the path planning of industrial robots, and the operating efficiency of robots controlled by different target routes can be periodically compared. When the efficiency deviation is obvious when the robot is controlled by a stable target route, a target route that takes both stability and efficiency into consideration is generated to further improve the overall operating efficiency of industrial robots in industrial workshops. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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 some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0018] Embodiment 1 like Figure 1 As shown, a process auxiliary planning system based on visual positioning includes an auxiliary planning platform, which is communicatively connected to a positioning analysis module, a path monitoring module, a path analysis module and a database.

[0019] The positioning analysis module is used to perform positioning analysis on each target object in the industrial workshop: take a bird's-eye view image of the industrial workshop and mark the obtained image as a positioning image, enlarge the positioning image into a pixel grid image and perform grayscale transformation, use a binary method to extract the edge information of the industrial robot and the target workstation in the positioning image and mark the positions of the industrial robot and the target workstation, and then extract the robot path information in the positioning image. The robot path information includes several robot-specific channels, and the robot-specific channels are marked by two parallel marking coils; the industrial robot position information, the target workstation path information and the robot path information constitute a positioning information group and send the positioning information group to the path monitoring module through the auxiliary planning platform; take an image according to the industrial workshop, use image processing technology to process the positioning image to obtain positioning information, so as to provide data support for path monitoring analysis and path planning analysis through the positioning information.

[0020] The path monitoring module is used to perform obstruction analysis on the robot-dedicated channel in the industrial workshop: the grayscale range of obstacles is retrieved through the database, and the area between the two marking lines of the robot-dedicated channel is marked as the monitoring area. The pixel grids in the monitoring area whose grayscale values ​​are within the grayscale range of obstacles are marked as obstruction grids. The obstruction grids that touch each other form an obstruction area, and the coverage data FG and the concentrated data JZ of the monitoring area are obtained. The coverage data FG is the total number of obstruction grids in the monitoring area. The acquisition process of the concentrated data JZ includes: marking the number of obstruction grids in the obstruction area as the concentrated value of the obstruction area, and marking the maximum value of the concentrated values ​​in all obstruction areas as the concentrated data JZ; the obstruction coefficient ZA of the monitoring area is obtained by the formula ZA=k1*JZ+k2*FG. Among them, k1 and k2 are both proportional coefficients, and k1>k2>1; the obstruction threshold ZAmax is retrieved from the database, and the obstruction coefficient ZA of the monitoring area is compared with the obstruction threshold ZAmax: if the obstruction coefficient ZA is less than the obstruction threshold ZAmax, the corresponding robot-specific channel is marked as a normal channel; if the obstruction coefficient ZA is greater than or equal to the obstruction threshold ZAmax, the corresponding robot-specific channel is marked as an obstruction channel, and all obstruction channels are deleted from the positioning information; the obstruction coefficient is obtained by comprehensive analysis and calculation based on multiple obstruction data in the monitoring area, and then the overall smoothness of the monitoring area is fed back through the obstruction coefficient, and the robot-specific channel in the positioning information is updated according to the feedback results to avoid obstruction of robot operation after route generation.

[0021] The path analysis module is used to plan and analyze the driving routes of industrial robots in industrial workshops: generate several driving routes based on the industrial robot position information, target workstation path information and updated robot path information in the positioning information, and then mark the industrial robot as the analysis object, obtain the load data FZ and space data KJ of the analysis object, the load data FZ is the weight value of the load on the analysis object, and the space data KJ is the volume value of the load on the analysis object; the stability coefficient PW of the analysis object is obtained by the formula PW=m1*FZ+m2*KJ, where m1 and m2 are both proportional coefficients, and m1>m2>1; retrieve the stability threshold PWmax from the database, and compare the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, the analysis is determined. If the load stability of the object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, and the driving route with the smallest switching value is marked as the stability target route; the efficiency target route or the stability target route is sent to the industrial robot control terminal; the driving route of the industrial robot in the industrial workshop is planned and analyzed and the stability coefficient is obtained. The stability requirement degree of the analysis object during operation is evaluated through the stability coefficient, and then different methods are adopted according to the evaluation results to generate the corresponding target route, match the targeted recommended routes under different operating environments, and improve the actual operating efficiency of the industrial robot.

[0022] Embodiment 2 like Figure 2 As shown, the path analysis module is also communicatively connected to the industrial robot control terminal and the optimization analysis module.

[0023] After receiving the efficiency target route / stable target route, the industrial robot control terminal controls the industrial robot to move according to the efficiency target route / stable target route until the industrial robot reaches the target workstation.

[0024] The optimization analysis module is used to optimize the route planning of the industrial robot: the difference between the time when the industrial robot arrives at the target workstation and the time when the industrial robot control terminal receives the efficiency target route / smooth target route is marked as the time difference value of this execution process, the straight-line distance between the industrial robot and the target workstation before moving is marked as the path value of the execution process, and the ratio of the path value to the time difference value is marked as the execution coefficient of the execution process; an optimization cycle is generated, and the execution coefficients of all execution processes that use the efficiency target route for robot movement control in the optimization cycle are summed and averaged to obtain the efficiency priority value, and the execution coefficients of all execution processes that use the smooth target route for robot movement control in the optimization cycle are summed and averaged to obtain the smooth priority value, and the efficiency priority value is used as the average value. The difference with the smooth priority value is marked as the optimization necessary value, and the optimization necessary value is compared with the preset optimization necessary threshold: if the optimization necessary value is less than the optimization necessary threshold, it is determined that the path planning mode of the industrial robot within the optimization period is not necessary for optimization; if the optimization necessary value is greater than or equal to the optimization necessary threshold, it is determined that the path planning mode of the industrial robot within the optimization period is necessary for optimization, and a balanced optimization signal is generated and sent to the path analysis module; the operation efficiency of the robot controlled by different target routes is periodically compared. When the efficiency deviation is obvious when the robot operation is controlled by a smooth target route, a balanced target route is generated by taking into account both stability and efficiency, so as to further improve the overall operation efficiency of the industrial robot in the industrial workshop.

[0025] After receiving the balanced optimization signal, the path analysis module optimizes the path planning process of the analysis object in a specific process including: comparing the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, it is determined that the load stability of the analysis object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, the driving routes are arranged in order of driving distance from short to long to obtain an efficiency sequence, the driving routes are sorted in order of switching value from small to large to obtain a switching sequence, the sum of the serial numbers of the driving routes in the efficiency sequence and the switching sequence is marked as the balanced value, and the driving route with the smallest balanced value is marked as the balanced target route; the efficiency target route or the balanced target route is sent to the industrial robot control terminal.

[0026] After receiving the efficiency target route / combination target route, the industrial robot control terminal controls the industrial robot to move according to the efficiency target route / combination target route until the industrial robot reaches the target workstation.

[0027] A process auxiliary planning system and method based on visual positioning, when working, performs positioning analysis on each target object in an industrial workshop and obtains positioning information, performs obstruction analysis on robot-specific channels in the industrial workshop and marks the robot-specific channels in the robot path information as normal channels or obstruction channels, deletes the obstruction channels from the positioning information, and then calculates the stability coefficient PW of the analysis object, generates an efficiency target route or a stability target route according to the stability coefficient PW, and controls the industrial robot according to the efficiency target route or the stability target route.

[0028] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0029] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula PW=m1*FZ+m2*KJ; technicians in this field collect multiple groups of sample data and set corresponding stability coefficients for each group of sample data; substitute the set stability coefficients and the collected sample data into the formula, any two formulas constitute a set of two-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of m1 and m2 as 3.05 and 2.82 respectively; The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the technical personnel in this field preliminarily setting the corresponding stability coefficient for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the stability coefficient is proportional to the value of the load data.

[0030] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0031] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A process-assisted planning system and method based on visual positioning, characterized in that: It includes an auxiliary planning platform, which is communicatively connected with a positioning analysis module, a path monitoring module, a path analysis module and a database; The positioning analysis module is used to perform positioning analysis on each target object in the industrial workshop and obtain; the industrial robot position information, target station path information and robot path information constitute a positioning information group and send the positioning information group to the path monitoring module through the auxiliary planning platform; The path monitoring module is used to perform obstruction analysis on robot-specific channels in the industrial workshop: marking robot-specific channels in the robot path information as normal channels or obstruction channels, and deleting all obstruction channels from the positioning information; The path analysis module is used to plan and analyze the driving routes of industrial robots in industrial workshops: generate several driving routes according to the industrial robot position information, target workstation path information and updated robot path information in the positioning information, then mark the industrial robot as an analysis object, obtain the stability coefficient PW of the analysis object, determine whether the load stability of the analysis object meets the requirements through the stability coefficient PW, and generate an efficiency target route or a stability target route.

2. A process-assisted planning system and method based on visual positioning according to claim 1, characterized in that: The process of acquiring the industrial robot position information, target workstation path information and robot path information includes: taking a bird's-eye view image of the industrial workshop and marking the obtained image as a positioning image, enlarging the positioning image into a pixel grid image and performing a grayscale transformation, using a binary method to extract the edge information of the industrial robot and the target workstation in the positioning image and marking the positions of the industrial robot and the target workstation, and then extracting the robot path information in the positioning image. The robot path information includes several robot-specific channels, which are defined by two parallel marking coils.

3. A process-assisted planning system and method based on visual positioning according to claim 2, characterized in that: The specific process of marking the robot-only channel as a normal channel or an obstruction channel includes: retrieving the grayscale range of obstacles through the database, marking the area between the two marking lines of the robot-only channel as the monitoring area, and obtaining the obstruction coefficient ZA of the monitoring area; retrieving the obstruction threshold ZAmax through the database, and comparing the obstruction coefficient ZA of the monitoring area with the obstruction threshold ZAmax: if the obstruction coefficient ZA is less than the obstruction threshold ZAmax, the corresponding robot-only channel is marked as a normal channel; if the obstruction coefficient ZA is greater than or equal to the obstruction threshold ZAmax, the corresponding robot-only channel is marked as an obstruction channel.

4. A process-assisted planning system and method based on visual positioning according to claim 3, characterized in that: The process of obtaining the obstruction coefficient ZA of the monitoring area includes: marking the pixel grids whose grayscale values ​​in the monitoring area are within the grayscale range of the obstacle as obstruction grids, forming an obstruction area by the obstruction grids that are in contact with each other, obtaining the coverage data FG and the concentrated data JZ of the monitoring area, the coverage data FG is the total number of obstruction grids in the monitoring area, and the process of obtaining the concentrated data JZ includes: marking the number of obstruction grids in the obstruction area as the concentrated value of the obstruction area, and marking the maximum value of the concentrated values ​​in all obstruction areas as the concentrated data JZ; the obstruction coefficient ZA of the monitoring area is obtained by the formula ZA=k1*JZ+k2*FG, wherein k1 and k2 are both proportional coefficients, and k1>k2>1.

5. A process-assisted planning system and method based on visual positioning according to claim 4, characterized in that: The process of obtaining the stability coefficient PW of the analysis object includes: obtaining the weight data FZ and space data KJ of the analysis object, the weight data FZ is the weight value of the load on the analysis object, and the space data KJ is the volume value of the load on the analysis object; the stability coefficient PW of the analysis object is obtained by the formula PW=m1*FZ+m2*KJ, where m1 and m2 are both proportional coefficients, and m1>m2>1.

6. A process-assisted planning system and method based on visual positioning according to claim 5, characterized in that: The specific process of determining whether the load stability of the analysis object meets the requirements includes: retrieving the stability threshold PWmax through the database, and comparing the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, then it is determined that the load stability of the analysis object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, then it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, and the driving route with the smallest switching value is marked as the stability target route.

7. A process-assisted planning system and method based on visual positioning according to claim 6, characterized in that: The path analysis module is also communicatively connected to the industrial robot control terminal and the optimization analysis module; After receiving the efficiency target route / stable target route, the industrial robot control terminal controls the industrial robot to move according to the efficiency target route / stable target route until the industrial robot reaches the target workstation; The optimization analysis module is used to optimize and analyze the route planning of the industrial robot: mark the difference between the time when the industrial robot arrives at the target workstation and the time when the industrial robot control terminal receives the efficiency target route / smooth target route as the time difference value of this execution process, mark the straight-line distance between the industrial robot and the target workstation before moving as the path value of the execution process, and mark the ratio of the path value to the time difference value as the execution coefficient of the execution process; generate an optimization cycle, sum and average the execution coefficients of all execution processes that use the efficiency target route to control the robot's movement within the optimization cycle to obtain an efficiency priority value, sum and average the execution coefficients of all execution processes that use the smooth target route to control the robot's movement within the optimization cycle to obtain a smooth priority value, mark the difference between the efficiency priority value and the smooth priority value as the necessary optimization value, and compare the necessary optimization value with the preset necessary optimization threshold: if the necessary optimization value is less than the necessary optimization threshold, it is determined that the path planning mode of the industrial robot within the optimization cycle does not have the necessity of optimization; If the optimization necessity value is greater than or equal to the optimization necessity threshold, it is determined that the path planning mode of the industrial robot within the optimization period has the necessity of optimization, and a balanced optimization signal is generated and sent to the path analysis module.

8. A process-assisted planning system and method based on visual positioning according to claim 7, characterized in that: After receiving the balanced optimization signal, the path analysis module optimizes the path planning process of the analysis object in a specific process including: comparing the stability coefficient PW of the analysis object with the stability threshold PWmax: if the stability coefficient PW is less than the stability threshold PWmax, it is determined that the load stability of the analysis object meets the requirements, the driving distances of all driving routes are obtained, and the driving route with the shortest driving distance is marked as the efficiency target route; if the stability coefficient PW is greater than or equal to the stability threshold PWmax, it is determined that the load stability of the analysis object does not meet the requirements, the number of robot-specific channel switching times of all driving routes is obtained and marked as the switching value, the driving routes are arranged in order of driving distance from short to long to obtain an efficiency sequence, the driving routes are sorted in order of switching value from small to large to obtain a switching sequence, the sum of the serial numbers of the driving routes in the efficiency sequence and the switching sequence is marked as the balanced value, and the driving route with the smallest balanced value is marked as the balanced target route; the efficiency target route or the balanced target route is sent to the industrial robot control terminal.

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