Automatic inspection control method and system for robot

Abstract

The invention belongs to the technical field of robot control, and particularly relates to an automatic inspection control method and system for a robot, and the method comprises the steps: starting the robot to move according to a preset inspection region and a preset initial exploration path, and constructing a two-dimensional inspection region map; according to the constructed map, an improved A * algorithm is adopted for routing inspection path planning; after path planning is completed, a personalized inspection task list is set according to the type, importance degree and operation parameter requirements of equipment in the inspection area, and a robot inspection path is determined according to the personalized inspection task list for automatic inspection; the robot collects equipment operation data and state information in the inspection process in the automatic inspection process and sends the equipment operation data and the state information to the inspection data monitoring center for data analysis, and after inspection is finished, the robot automatically navigates and returns to the charging pile for charging. Through combination of the improved A * algorithm and the personalized inspection task list, automatic inspection control of the dynamic robot is realized, and the inspection efficiency of the robot is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of robot control, and in particular relates to an automatic inspection control method and system for a robot. Background Art

[0002] In many industrial scenarios and large facilities, such as warehouses, power distribution rooms, factory production lines, etc., regular inspections are required to ensure the normal operation of equipment and the safety of the environment. Traditional manual inspection methods not only consume a lot of manpower, but are also inefficient and prone to missed inspections and misjudgments. In some industrial scenarios, such as chemical and pharmaceutical industries, there is no communication network to transmit the operating data of the equipment to the monitoring background, and the inspectors face a harsh working environment when inspecting the equipment, which poses a health risk to the inspectors. Therefore, a safe equipment inspection method that does not require human intervention is needed.

[0003] With the development of robot technology, using robots for automatic inspection has gradually become a trend, but the current robot inspection methods still have many shortcomings in robot inspection control and path planning. In addition, the current robot inspection methods are mostly limited to completing the inspection of equipment by taking pictures of the equipment with cameras installed on the robot, and are unable to obtain the equipment's operating data. It is impossible to accurately determine whether the equipment has an operating failure just by taking pictures of the equipment, and it is difficult to meet the complex and changeable actual needs. Summary of the invention

[0004] In view of the shortcomings of the above-mentioned existing methods, the present invention provides an automatic patrol control method for a robot, aiming to solve the core problems in the prior art of low robot patrol efficiency, inability to obtain patrol equipment operation data, fixed patrol path, low applicability and insufficient robot patrol controllability.

[0005] To achieve the above-mentioned purpose, the present invention is implemented by the following technical solutions: A robot automatic inspection control method, the method comprising the following steps: Step S10: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a two-dimensional inspection area map; Step S20: using an improved A* algorithm to plan inspection paths based on the constructed two-dimensional inspection area map; Step S30: After the path planning is completed, a personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the robot inspection path is determined according to the personalized inspection task list for automatic inspection; Step S40: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends them to the inspection data monitoring center for data analysis. According to the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging pile for charging. Among them, the various sensors installed on the robot in step S10 include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera takes real-time photos of the environment on the robot's path to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the camera's blind spot; the various types of information collected are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map; Among them, the data analysis performed by the inspection data monitoring center in step S40 includes presetting a parameter threshold T for normal operation of the equipment. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After the first round of inspection, the equipment is inspected for a second time. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued and professional operators perform fault repairs; when the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, the equipment operation data collected in the two rounds of inspection is recorded and marked as having potential faults, and professional operators focus on troubleshooting it during regular equipment maintenance.

[0006] Preferably, the step of constructing a two-dimensional inspection area map using a grid method in step S10 includes: Determine the grid size and area: Determine the grid size according to the size of the inspection area and the inspection accuracy requirements of the robot, and divide the plane space of the inspection area into regular grids of the same size according to the determined grid size. For example, if the inspection area is a large warehouse with a length of 50 meters and a width of 30 meters, and the robot is equipped with a high-precision laser radar with a ranging accuracy of 0.05 meters, the grid size can be set to 0.5 meters × 0.5 meters; Map information annotation: Based on the information collected by various sensors installed on the robot, the location and range of obstacles in the inspection area are determined. When there is an obstacle in the grid, the grid is marked as an "obstacle grid" and the binary value "1" is used to indicate the obstacle; when there is no obstacle in the grid, the grid is marked as a "passing area grid" and the binary value "0" is used to indicate the passing area; Map information storage: Use a two-dimensional array to store grid map information. Each element in the two-dimensional array corresponds to a grid. The array is stored in the built-in memory of each robot. Map update mechanism: The sensors installed on the robot continuously collect environmental information of the inspection area during the inspection process and update the two-dimensional inspection area map in real time.

[0007] Preferably, the step of using the improved A* algorithm to perform inspection path planning according to the constructed two-dimensional inspection area map in step S20 includes: Map data import and initialization: Import the constructed two-dimensional inspection area map into the robot inspection path planning unit. The two-dimensional inspection area map includes the equipment location, inspection channel and obstacle location information. The initialization robot's starting point coordinates are (X start ,Y start ), set the charging pile coordinates to (X charge ,Y charge ), set the detection point coordinates of the equipment to be detected in the inspection area to (X test ,Y test ) Initialize the weight coefficient W of the heuristic function in the A* algorithm parameters. This coefficient is used to balance the exploration and utilization tendencies in the path planning process to meet the needs of path optimality in different scenarios. Usually, the value range of W is between 0 and 1. When W is close to 0, the algorithm is more inclined to use existing information and give priority to exploring paths closer to the target; when W is close to 1, the algorithm is more inclined to explore unknown areas, find more potential paths and increase the algorithm's computing time; Set robot motion parameters: After completing map data import and initialization, set the robot's motion direction and motion parameters in the map. The motion parameters include the range of angle changes when the robot moves between adjacent grids. ,in is the minimum angle when the robot moves between adjacent grids, is the angle at which the robot moves between adjacent grids, is the maximum angle of the robot when it moves between adjacent grids; the maximum moving speed of the robot V max and acceleration a max Parameters such as , ensure that the planned path is the path that the robot can actually walk.

[0008] Heuristic function design: Improve the heuristic function of the traditional A* algorithm. In addition to considering the Euclidean distance from the current grid to the target detection point, more factors related to the actual inspection environment are considered. Introduce the battery power consumption factor, establish a battery power consumption model, and set the power consumption coefficient e for the robot at unit distance and different terrains. For example, when the robot is on flat ground, e = 0.1 unit power / meter; when the robot is on a slope and climbing, e = 0.2 unit power / meter; when the robot is on a slope and going downhill, e = 0.05 unit power / meter. The battery power consumption model is shown in Equation (1): (1) where d is the Euclidean distance from the current grid to the target detection point; Introduce the safety factor of the robot inspection path. For the area close to the obstacle, set the risk penalty value r, which is inversely proportional to the distance d from the robot's current position to the nearest obstacle to the robot's current position, as shown in Equation (2): risk as follows: (2) where k is the risk coefficient, and its value is set according to the actual inspection environment of the robot and 0 < k < 10. For example, in an area with dense obstacles, k = 8; in an area with sparse obstacles, k = 3. The denser the obstacles or the closer to the obstacles, the greater the risk penalty value. The improved heuristic function is shown in Equation (3): (3) where h is the improved heuristic function; Robot inspection path planning: Start from the starting point, put the current grid into an open list, and calculate the evaluation value f of each grid in the open list through the set heuristic function, as shown in Equation (4): (4) where g is the actual path cost from the starting point of the robot inspection to the current grid, and c is the estimated cost from the starting point of the robot inspection to the target detection point. Select the grid with the highest evaluation value f in the open list for expansion, add its adjacent passable area grids to the open list, and recalculate and update the parent node pointer, the actual path cost g, and the evaluation value f; Move the calculated grids to the closed list to avoid repeated exploration; Continuously check whether the current grid is the target detection point during the path planning process. When the current grid is the target detection point, construct a complete inspection path by backtracking the parent node pointer; Path determination: Set the path score Score to screen the planned path, and select the path with the highest score as the robot inspection path. The calculation formula of the path score Score is shown in Equation (5): (5) in, is the path length weight, is the battery power consumption weight, is the safety weight, and + + =1, L is the path length, E is the robot battery power consumption, and S is the safety value; the selected inspection path is stored in the robot's control system, and the robot navigates to each equipment detection point according to the stored inspection path for automatic inspection.

[0009] Preferably, after the path planning in step S30 is completed, a personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the step of determining the robot inspection path for automatic inspection according to the personalized inspection task list includes: Equipment information collection and classification: Collect and record the types and operating parameter requirements of all equipment in the inspection area, and classify the equipment into Class A, Class B, and Class C according to their importance in the production process; Equipment task list setting: For equipment with A-level importance, set it to be inspected every 15 minutes, for equipment with B-level importance, set it to be inspected every 30 minutes, and for equipment with C-level importance, set it to be inspected every 60 minutes. The robot collects different data for different equipment during inspection, and sets the corresponding execution actions when the robot collects data; Task list integration and optimization: Arrange the set equipment task list in the order of the inspection path to ensure that the robot can efficiently and smoothly shuttle between the devices during inspection, reducing unnecessary return and waiting time; Task list storage and update: The set equipment task list is stored in the robot's control system so that the robot can retrieve and execute it at any time during the inspection process; the equipment task list is updated every 24 hours, such as equipment upgrades, changes in operating conditions (such as seasonal load adjustments, process improvements) or new maintenance requirements. For example, when a more advanced transformer is newly installed, its operating parameters and inspection requirements are different from those of the old equipment, and the task list needs to be adjusted to ensure the effectiveness and accuracy of the inspection.

[0010] Preferably, in step S40, the robot collects all equipment operation data during the automatic inspection process. Various sensors are installed in the equipment to collect the equipment operation data and store it in the equipment operation data module. When the robot arrives at the detection point of the equipment, it communicates with the built-in communication module of the equipment. After the connection is successful, the robot adjusts its posture according to the set task and collects the equipment operation data stored in the equipment operation data module through an external data acquisition unit.

[0011] In addition, to achieve the above-mentioned purpose, the present invention also proposes an automatic inspection control system of a robot, the automatic inspection control system of the robot comprising: 2D inspection area map construction module: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a 2D inspection area map; Path planning module: Based on the constructed two-dimensional inspection area map, the improved A* algorithm is used to plan the inspection path; Personalized inspection task list setting module: After the path planning is completed, the personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the robot inspection path is determined according to the personalized inspection task list for automatic inspection; Robot automatic inspection module: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends them to the inspection data monitoring center for data analysis. Based on the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging station for charging. The various sensors installed on the robot in the two-dimensional inspection area map construction module include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera takes real-time photos of the environment on the robot's path to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the blind spot of the camera; the various types of information collected are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map; The data analysis performed by the inspection data monitoring center in the robot automatic inspection module includes presetting a parameter threshold T for normal operation of the equipment. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After the first round of inspection, a second round of inspection is performed on the equipment. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued and a professional operator performs fault repair. When the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, the equipment operation data collected in the two rounds of inspection is recorded and marked as having potential faults, and professional operators focus on troubleshooting during regular equipment maintenance.

[0012] In addition, to achieve the above-mentioned purpose, the present invention also proposes an automatic patrol control device for a robot, which includes: a memory, a processor, and programs such as an improved A* algorithm stored in the memory and run on the processor, and the improved A* algorithm and other programs are steps to implement a robot automatic patrol control method as described above.

[0013] Preferably, in order to achieve the above-mentioned purpose, the present invention also provides a computer program product, which includes programs such as an improved A* algorithm, and when the improved A* algorithm and other programs are executed by a processor, an automatic inspection control method of a robot as described above is implemented.

[0014] The advantages and effects of the present invention are: The present invention provides a robot automatic inspection control method and system. By combining an improved A* algorithm and a personalized inspection task list, a robot inspection route that is more in line with the actual inspection scenario can be planned, and the personalized inspection task list can be updated in real time according to the inspection results during the robot inspection process, thereby achieving precise robot inspection control and improving the efficiency of robot inspection. 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 The present invention is a flowchart of an automatic inspection control method for a robot.

[0017] Figure 2 The present invention is a schematic diagram of the structure of an automatic inspection control system of a robot.

[0018] Figure 3 The present invention is a schematic block diagram of the structure of an automatic inspection control electronic device for a robot. DETAILED DESCRIPTION

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

[0020] The present invention provides a robot automatic inspection control method, the method is composed as follows Figure 1 As shown, the following steps are included: Step S10: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a two-dimensional inspection area map.

[0021] Among them, the various sensors installed on the robot in step S10 include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera shoots the environment on the robot's travel path in real time to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the blind spot of the camera; the various types of collected information are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map.

[0022] Specifically, the step of constructing a two-dimensional inspection area map using the grid method in step S10 includes: Determine the grid size and area: Determine the grid size according to the size of the inspection area and the inspection accuracy requirements of the robot, and divide the plane space of the inspection area into regular grids of the same size according to the determined grid size. For example, if the inspection area is a large warehouse with a length of 50 meters and a width of 30 meters, and the robot is equipped with a high-precision laser radar with a ranging accuracy of 0.05 meters, the grid size can be set to 0.5 meters × 0.5 meters; Map information annotation: Based on the information collected by various sensors installed on the robot, the location and range of obstacles in the inspection area are determined. When there is an obstacle in the grid, the grid is marked as an "obstacle grid" and the binary value "1" is used to indicate the obstacle; when there is no obstacle in the grid, the grid is marked as a "passing area grid" and the binary value "0" is used to indicate the passing area; Map information storage: Use a two-dimensional array to store grid map information. Each element in the two-dimensional array corresponds to a grid. The array is stored in the built-in memory of each robot. Map update mechanism: The sensors installed on the robot continuously collect environmental information of the inspection area during the inspection process and update the two-dimensional inspection area map in real time.

[0023] Step S20: using an improved A* algorithm to plan inspection paths based on the constructed two-dimensional inspection area map.

[0024] Specifically, the step of using the improved A* algorithm to perform inspection path planning according to the constructed two-dimensional inspection area map in step S20 includes: Map data import and initialization: Import the constructed two-dimensional inspection area map into the robot inspection path planning unit. The two-dimensional inspection area map includes the equipment location, inspection channel and obstacle location information. The initialization robot's starting point coordinates are (X start ,Y start ), set the charging pile coordinates to (X charge ,Y charge ), set the detection point coordinates of the equipment to be detected in the inspection area to (X test ,Y test ) Initialize the weight coefficient W of the heuristic function in the A* algorithm parameters. This coefficient is used to balance the exploration and utilization tendencies in the path planning process to meet the needs of path optimality in different scenarios. Usually, the value range of W is between 0 and 1. When W is close to 0, the algorithm is more inclined to use existing information and give priority to exploring paths closer to the target; when W is close to 1, the algorithm is more inclined to explore unknown areas, find more potential paths and increase the algorithm's computing time; Set robot motion parameters: After completing map data import and initialization, set the robot's motion direction and motion parameters in the map. The motion parameters include the range of angle changes when the robot moves between adjacent grids. ,in is the minimum angle when the robot moves between adjacent grids, is the angle at which the robot moves between adjacent grids, is the maximum angle of the robot when it moves between adjacent grids; the maximum moving speed of the robot V max and acceleration a max Parameters such as , ensure that the planned path is the path that the robot can actually walk.

[0025] Heuristic function design: The heuristic function of the traditional A* algorithm is improved. In addition to considering the Euclidean distance from the current grid to the target detection point, more factors related to the actual inspection environment are considered. The battery power consumption factor is introduced to establish a battery power consumption model. The power consumption coefficient of the robot in unit distance and different terrains is set to e. For example, when the robot is on a flat ground, e=0.1, unit power / meter; when the robot is on a slope and climbing, e=0.2, unit power / meter; when the robot is on a slope and downhill, e=0.05, unit power / meter. The battery power consumption model is shown in formula (1): (1) Where d is the Euclidean distance from the current grid to the target detection point; Introducing the safety factor of the robot inspection path, setting the risk penalty value r for the area close to obstacles and the distance d from the robot's current position to the nearest obstacle to the robot's current position riskinversely proportional, as shown in Equation (2): (2) where k is the risk coefficient, and its value is set according to the actual inspection environment of the robot, and 0 < k < 10. For example, in an area with dense obstacles, k = 8, and in an area with sparse obstacles, k = 3. The denser the obstacles or the closer to the obstacles, the greater the risk penalty value; the improved heuristic function is as shown in Equation (3): (3) where h is the improved heuristic function; Robot inspection path planning: Starting from the starting point, put the current grid into an open list, and calculate the evaluation value f of each grid in the open list through the set heuristic function, as shown in Equation (4): (4) where g is the actual path cost from the starting point of the robot inspection to the current grid, and c is the estimated cost from the starting point of the robot inspection to the target detection point. Select the grid with the highest evaluation value f in the open list for expansion, add its adjacent passable area grids to the open list, and recalculate and update the parent node pointer, the actual path cost g, and the evaluation value f; move the calculated grids to the closed list to avoid repeated exploration; continuously check whether the current grid is the target detection point during the path planning process. When the current grid is the target detection point, construct a complete inspection path by backtracking the parent node pointer; Path determination: Set a path score Score to screen the planned path, and select the path with the highest score as the robot inspection path. The calculation formula of the path score Score is as shown in Equation (5): (5) where, is the path length weight, is the battery power consumption weight, is the safety weight, and + + = 1, L is the path length, E is the battery power consumption of the robot, and S is the safety value; store the selected inspection path in the control system of the robot, and the robot navigates to each device detection point according to the stored inspection path for automatic inspection.

[0026] Step S30: After the path planning is completed, set a personalized inspection task list according to the types, importance levels, and operating parameter requirements of the devices in the inspection area, and determine the robot inspection path according to the personalized inspection task list for automatic inspection.

[0027] Specifically, after the path planning in step S30 is completed, a personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the step of determining the robot inspection path for automatic inspection according to the personalized inspection task list includes: Equipment information collection and classification: Collect and record the types and operating parameter requirements of all equipment in the inspection area, and classify the equipment into Class A, Class B, and Class C according to their importance in the production process; Equipment task list setting: For equipment with A-level importance, set it to be inspected every 15 minutes, for equipment with B-level importance, set it to be inspected every 30 minutes, and for equipment with C-level importance, set it to be inspected every 60 minutes. The robot collects different data for different equipment during inspection, and sets the corresponding execution actions when the robot collects data; Task list integration and optimization: Arrange the set equipment task list in the order of the inspection path to ensure that the robot can efficiently and smoothly shuttle between the devices during inspection, reducing unnecessary return and waiting time; Task list storage and update: The set equipment task list is stored in the robot's control system so that the robot can retrieve and execute it at any time during the inspection process; the equipment task list is updated every 24 hours, such as equipment upgrades, changes in operating conditions (such as seasonal load adjustments, process improvements) or new maintenance requirements. For example, when a more advanced transformer is newly installed, its operating parameters and inspection requirements are different from those of the old equipment, and the task list needs to be adjusted to ensure the effectiveness and accuracy of the inspection.

[0028] Step S40: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends it to the inspection data monitoring center for data analysis. According to the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging pile for charging.

[0029] Specifically, the data analysis performed by the inspection data monitoring center in step S40 includes presetting a parameter threshold T for normal equipment operation. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After one round of inspection, a second round of inspection is performed on the equipment. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued and professional operators perform fault repair. When the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, and the equipment operation data collected in the two rounds of inspection is recorded and marked as having potential faults. Professional operators focus on troubleshooting the equipment during regular equipment maintenance.

[0030] Specifically, in step S40, the robot collects all equipment operation data during the automatic inspection process. Various sensors are installed in the equipment to collect the equipment operation data and store it in the equipment operation data module. When the robot arrives at the detection point of the equipment, it communicates with the built-in communication module of the equipment. After the connection is successful, the robot adjusts its posture according to the set task and collects the equipment operation data stored in the equipment operation data module through an external data acquisition unit.

[0031] In addition, the present invention also proposes an automatic inspection control system of a robot, please refer to Figure 2 , the automatic inspection control system of the robot comprises: 2D inspection area map construction module: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a 2D inspection area map; Path planning module: Based on the constructed two-dimensional inspection area map, the improved A* algorithm is used to plan the inspection path; Personalized inspection task list setting module: After the path planning is completed, the personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the robot inspection path is determined according to the personalized inspection task list for automatic inspection; Robot automatic inspection module: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends them to the inspection data monitoring center for data analysis. Based on the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging station for charging. The various sensors installed on the robot in the two-dimensional inspection area map construction module include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera takes real-time photos of the environment on the robot's path to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the blind spot of the camera; the various types of information collected are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map; The data analysis performed by the inspection data monitoring center in the robot automatic inspection module includes presetting a parameter threshold T for normal operation of the equipment. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After the first round of inspection, a second round of inspection is performed on the equipment. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued and a professional operator performs fault repair. When the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, the equipment operation data collected in the two rounds of inspection is recorded and marked as having potential faults, and professional operators focus on troubleshooting during regular equipment maintenance.

[0032] The present application provides a robot automatic inspection control system, which adopts a robot automatic inspection control method in the above embodiment, and can solve the technical problems of low robot inspection control efficiency, low path planning applicability, and insufficient flexibility. Compared with the prior art, the beneficial effects of the robot automatic inspection control system provided by the present application are the same as the beneficial effects of the robot automatic inspection control method provided by the above embodiment, and the other technical features of the robot automatic inspection control system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0033] The present application provides an automatic inspection control device for a robot, the automatic inspection control device for a robot comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the automatic inspection control method for a robot in the above-mentioned embodiment one.

[0034] Reference below Figure 3 , which shows a schematic diagram of the structure of an automatic inspection control device of a robot suitable for implementing an embodiment of the present application. The automatic inspection control device of a robot in an embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The automatic inspection control device of a robot shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0035] Figure 3 The automatic inspection control device of a robot shown may include a processing system 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage system 1003 to a random access memory (RAM) 1004. Various programs and data required for the operation of the automatic inspection control device of a robot are also stored in the RAM 1004. The processing system 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: an input system 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output system 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage system 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication system 1009. The communication system 1009 may allow a robot's automatic inspection control device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a robot's automatic inspection control device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0036] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication system, or installed from a storage system 1003, or installed from a ROM 1002. When the computer program is executed by the processing system 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0037] The present application provides a robot automatic inspection control device, which adopts a robot automatic inspection control method in the above embodiment, and can solve the technical problems of low robot inspection control efficiency, low path planning applicability, and insufficient flexibility. Compared with the prior art, the beneficial effects of the robot automatic inspection control device provided by the present application are the same as the beneficial effects of the robot automatic inspection control method provided by the above embodiment, and the other technical features of the robot automatic inspection control device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0038] The various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0039] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the automatic inspection control method of a robot as described above.

[0040] The computer program product provided by the present application can solve the technical problems of low efficiency of robot inspection control, low applicability of path planning, and insufficient flexibility. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the automatic inspection control method of a robot provided in the above embodiment, which will not be described in detail here.

[0041] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A robot automatic inspection control method, characterized in that: The method comprises the following steps: Step S10: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a two-dimensional inspection area map; Step S20: using an improved A* algorithm to plan inspection paths based on the constructed two-dimensional inspection area map; Step S30: After the path planning is completed, a personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the robot inspection path is determined according to the personalized inspection task list for automatic inspection; Step S40: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends them to the inspection data monitoring center for data analysis. According to the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging pile for charging. The various sensors installed on the robot in step S10 include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera takes real-time photos of the environment on the robot's path to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the camera's blind spot; the various types of information collected are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map; The data analysis performed by the inspection data monitoring center in step S40 includes presetting a parameter threshold T for normal operation of the equipment. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After the first round of inspection, a second round of inspection is performed on the equipment. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued; when the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, and the equipment operation data collected in the two inspections are recorded and marked as having a potential fault.

2. The automatic inspection control method of a robot according to claim 1, characterized in that: In step S10, a two-dimensional inspection area map is constructed using a grid method, and the steps include: Determine the grid size and area: Determine the grid size according to the area occupied by the inspection area and the inspection accuracy requirements of the robot, and divide the plane space of the inspection area into regular grids of the same size according to the determined grid size; Map information annotation: Based on the information collected by various sensors installed on the robot, the location and range of obstacles in the inspection area are determined. When there is an obstacle in the grid, the grid is marked as an "obstacle grid" and a binary value of "1" is used to indicate an obstacle; when there is no obstacle in the grid, the grid is marked as a "passing area grid" and a binary value of "0" is used to indicate a passing area; Map information storage: Use a two-dimensional array to store grid map information. Each element in the two-dimensional array corresponds to a grid. The array is stored in the built-in memory of each robot. Map update mechanism: The sensors installed on the robot continuously collect the environmental information of the inspection area during the inspection process, and update the two-dimensional inspection area map in real time.

3. The automatic inspection control method of a robot according to claim 1, characterized in that: The steps of performing inspection path planning using the improved A* algorithm according to the constructed two-dimensional inspection area map in step S20 include: Map data import and initialization: Import the constructed two-dimensional inspection area map into the robot inspection path planning unit. The two-dimensional inspection area map includes the equipment location, inspection channel and obstacle location information. The initialization robot's starting point coordinates are (X start ,Y start ), set the charging pile coordinates to (X charge ,Y charge ), set the detection point coordinates of the equipment to be detected in the inspection area to (X test ,Y test );Initialize the weight coefficient W of the heuristic function in the A* algorithm parameters; Set robot motion parameters: After completing map data import and initialization, set the robot's motion direction and motion parameters in the map. The motion parameters include the range of angle changes when the robot moves between adjacent grids. ,in is the minimum angle when the robot moves between adjacent grids, is the angle at which the robot moves between adjacent grids, is the maximum angle of the robot when it moves between adjacent grids; the maximum moving speed of the robot V max and acceleration a max ; Heuristic function design: Improve the heuristic function of the traditional A* algorithm, introduce the battery power consumption factor, establish a battery power consumption model, and set the power consumption coefficient of the robot at unit distance and different terrains as e. The battery power consumption model is shown in Equation (1): （1） Where d is the Euclidean distance from the current grid to the target detection point; the safety factor of the robot inspection path is introduced, and the risk penalty value r is set for the area close to the obstacle, and the distance d from the current position of the robot to the nearest obstacle to the current position of the robot is set risk Inversely proportional, as shown in formula (2): （2） where k is the risk coefficient, and its value is set according to the actual inspection environment of the robot and 0 < k < 10; the improved heuristic function is shown in Equation (3): （3） where h is the improved heuristic function; Robot inspection path planning: Starting from the starting point, put the currently located grid into an open list, and calculate the evaluation value f of each grid in the open list through the set heuristic function, as shown in Equation (4): （4） where g is the actual path cost from the starting point of the robot inspection to the current grid, and c is the estimated cost from the starting point of the robot inspection to the target detection point. Select the grid with the highest evaluation value f in the open list for expansion, add its adjacent passable area grids to the open list, recalculate and update the parent node pointer, the actual path cost g, and the evaluation value f; move the calculated grid to the closed list; continuously check whether the current grid is the target detection point during the path planning process. When the current grid is the target detection point, construct a complete inspection path by backtracking the parent node pointer; Path determination: Set a path score Score to screen the planned paths, and select the path with the highest score as the robot inspection path. The calculation formula of the path score Score is shown in Equation (5): （5） in, is the path length weight, is the battery power consumption weight, is the safety weight, and + + =1, L is the path length, E is the robot battery power consumption, and S is the safety value; the selected inspection path is stored in the robot's control system, and the robot navigates to each equipment detection point according to the stored inspection path for automatic inspection.

4. The automatic inspection control method of a robot according to claim 1, characterized in that: The steps of setting a personalized inspection task list according to the type, importance, and operating parameter requirements of the equipment in the inspection area and determining the robot inspection path for automatic inspection after the path planning in step S30 include: Equipment information collection and classification: Collect and record the types and operating parameter requirements of all equipment in the inspection area, and divide the importance according to the role of the equipment in the production process, which are divided into Class A, Class B, and Class C; Equipment task list setting: For equipment with an importance level of Class A, set to be inspected every 15 minutes; for equipment with an importance level of Class B, set to be inspected every 30 minutes; for equipment with an importance level of Class C, set to be inspected every 60 minutes. The robot collects different data for different equipment during inspection, and sets the corresponding execution actions when the robot collects data; Task list integration and optimization: Arrange the set equipment task lists in the order of the inspection path; Task list storage and update: Store the set equipment task list in the control system of the robot; update the equipment task list every 24 hours.

5. The automatic inspection control method of a robot according to claim 1, characterized in that: In step S40, the robot collects all equipment operation data during the automatic inspection process. Various sensors are installed in the equipment to collect the equipment operation data and store it in the equipment operation data module. When the robot arrives at the detection point of the equipment, it communicates with the built-in communication module of the equipment. After the connection is successful, the robot adjusts its posture according to the set task and collects the equipment operation data stored in the equipment operation data module through an external data acquisition unit.

6. A robot automatic inspection control system, characterized in that: The automatic inspection control system of the robot comprises: 2D inspection area map construction module: Start the robot equipped with various sensors, move it according to the preset initial exploration path according to the inspection area, and build a 2D inspection area map; Path planning module: Based on the constructed two-dimensional inspection area map, the improved A* algorithm is used to plan the inspection path; Personalized inspection task list setting module: After the path planning is completed, the personalized inspection task list is set according to the type, importance and operating parameter requirements of the equipment in the inspection area, and the robot inspection path is determined according to the personalized inspection task list for automatic inspection; Robot automatic inspection module: During the automatic inspection process, the robot collects all equipment operation data and status information during the inspection process and sends them to the inspection data monitoring center for data analysis. Based on the data analysis results, the robot's personalized inspection task list is updated and it is determined whether the equipment has a fault. After the inspection, the robot automatically navigates back to the charging station for charging. The various sensors installed on the robot in the two-dimensional inspection area map construction module include laser radar, camera and ultrasonic sensor; the laser radar scans the inspection area environment in real time to obtain the contour information of the inspection area environment; the camera takes real-time photos of the environment on the robot's path to identify obstacles, various signs and equipment appearance features; the ultrasonic sensor assists in detecting obstacles at close range and in the blind spot of the camera; the various types of information collected are integrated to construct a two-dimensional inspection area map, and the robot's inspection path, equipment location and obstacle information are marked on the map; The data analysis performed by the inspection data monitoring center in the robot automatic inspection module includes presetting a parameter threshold T for normal operation of the equipment. When the equipment operation data collected by the robot during one round of inspection is greater than or equal to the set threshold T, the current inspection task is updated to the last item in the inspection task list. After the first round of inspection, a second round of inspection is performed on the equipment. When the equipment operation data collected in the second round of inspection is greater than or equal to the set threshold T, an equipment fault alarm is issued; when the equipment operation data collected in the second round of inspection is less than the set threshold T, no equipment fault alarm is issued, and the equipment operation data collected in the two inspections are recorded and marked as having potential faults.

7. A robot automatic inspection control device, characterized in that: The automatic inspection control device of a robot comprises: a memory, a processor and a program of an improved A* algorithm stored in the memory and executable on the processor. When the improved A* algorithm program is executed by the processor, an automatic inspection control method of a robot as described in any one of claims 1 to 5 is implemented.

8. A computer program product, characterized in that The computer program product includes a program of an improved A* algorithm, and when the program of the improved A* algorithm is executed by a processor, an automatic inspection control method of a robot as described in any one of claims 1 to 5 is implemented.

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