CN116954234B - Robot inspection control method and system - Google Patents
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Abstract
The application relates to the technical field of intelligent control, and provides a robot inspection control method and a robot inspection control system. The method comprises the following steps: dividing and marking the global inspection scene information to obtain a target inspection point set, and planning the global inspection scene information to obtain target inspection planning path information; the inspection robot performs running inspection based on the target inspection planning path information to obtain a local inspection data stream, so as to analyze the data stream and output inspection optimization path information; the inspection robot performs continuous inspection based on the inspection optimization path information, acquires inspection running track information, performs track comparison analysis on the inspection running track information, acquires inspection comparison deviation, and performs tracking control on the inspection robot according to the inspection comparison deviation. By adopting the method, the route planning can be carried out through the combination of global routing inspection and local routing inspection, so that the comprehensiveness of the route planning is realized, the routing inspection route planning accuracy and the control accuracy of the robot are improved, and the routing inspection effect and the routing inspection efficiency are further ensured.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to a robot inspection control method and a robot inspection control system.
Background
With the development of artificial intelligence, the inspection work of multiple scenes such as a machine room, a factory building and a pipeline is changed from traditional manual inspection to intelligent inspection of a robot, so that a new stage of scale management, remote monitoring and real-time feedback is entered. Once the equipment is caught to have any abnormality in the robot inspection, the robot can immediately alarm in modes of short messages, voice and the like, and the robot can directly lead engineers to reach the fault position, so that the inspection time and the labor input cost are greatly reduced. However, the inspection path planning accuracy of the prior art robot is low, so that the inspection effect and the inspection efficiency are low.
Disclosure of Invention
Based on the above, it is necessary to provide a method and a system for controlling the inspection of a robot, which can realize the comprehensiveness of path planning, improve the accuracy of path planning and control of the inspection of the robot, and further ensure the inspection effect and inspection efficiency.
A method of robotic inspection control, the method comprising: monitoring and acquiring global inspection scene information through industrial visual equipment; dividing and marking the global inspection scene information to obtain a target inspection point set; performing path planning on the global inspection scene information based on the target inspection point set to obtain target inspection planning path information; obtaining a patrol robot, wherein the patrol robot performs running patrol based on the target patrol planning path information to obtain a local patrol data stream; the local inspection data stream and the target inspection planning path information are sent to a control console for analysis, and inspection optimization path information is output; the inspection robot performs continuous inspection based on the inspection optimization path information to acquire inspection running track information; and comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation.
A robotic inspection control system, the system comprising: the inspection scene acquisition module is used for acquiring global inspection scene information through monitoring of industrial visual equipment; the scene division marking module is used for dividing and marking the global inspection scene information to obtain a target inspection point set; the path planning module is used for carrying out path planning on the global inspection scene information based on the target inspection point set to obtain target inspection planning path information; the inspection data stream obtaining module is used for obtaining an inspection robot, and the inspection robot performs operation inspection based on the target inspection planning path information to obtain a local inspection data stream; the data flow analysis module is used for sending the local inspection data flow and the target inspection planning path information to a control console for analysis and outputting inspection optimization path information; the inspection running track acquisition module is used for continuously inspecting the inspection robot based on the inspection optimization path information to acquire inspection running track information; and the tracking control module is used for comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation.
The robot inspection control method and the system solve the technical problems of low inspection effect and low inspection efficiency caused by low inspection path planning accuracy of robots in the prior art, achieve path planning through the combination of global inspection and local inspection, realize comprehensiveness of path planning, improve the inspection path planning accuracy and control accuracy of the robots, and further guarantee the inspection effect and the inspection efficiency.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Fig. 1 is a schematic flow chart of a robot inspection control method in an embodiment.
Fig. 2 is a schematic flow chart of obtaining a target inspection point set in a robot inspection control method according to an embodiment.
Fig. 3 is a block diagram of a robot inspection control system in one embodiment.
Reference numerals illustrate: the system comprises a patrol scene acquisition module 11, a scene division marking module 12, a path planning module 13, a patrol data stream acquisition module 14, a data stream analysis module 15, a patrol running track acquisition module 16 and a tracking control module 17.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, the application provides a robot inspection control method, which comprises the following steps:
step S100: monitoring and acquiring global inspection scene information through industrial visual equipment;
specifically, with the development of artificial intelligence, the inspection work of multiple scenes such as a machine room, a factory building, a pipeline and the like is changed from traditional manual inspection to intelligent inspection of a robot, so that a new stage of scale management, remote monitoring and real-time feedback is entered. Once the equipment is caught to have any abnormality in the robot inspection, the robot can immediately alarm in modes of short messages, voice and the like, and the robot can directly lead engineers to reach the fault position, so that the inspection time and the labor input cost are greatly reduced. In order to acquire the whole information of the inspection scene of the robot, the overall inspection scene information is acquired through monitoring of industrial visual equipment, the industrial visual equipment is an industrial monitoring device, can be a high-precision monitoring camera, is high in image monitoring definition and high in speed, and accordingly the overall image information of the scene to be inspected, namely the overall inspection scene information, is acquired through monitoring, and a scene data basis is provided for follow-up inspection point marks.
Step S200: dividing and marking the global inspection scene information to obtain a target inspection point set;
in one embodiment, as shown in fig. 2, the obtaining the target set of inspection points, step S200 of the present application further includes:
step S210: performing space modeling based on the global inspection scene information to obtain an inspection scene three-dimensional model, and performing region division on the inspection scene three-dimensional model to generate an inspection scene segmentation region set;
step S220: respectively identifying patrol targets in the patrol scene segmentation area set to obtain a patrol target set;
step S230: acquiring characteristic attribute information of a target object, wherein the characteristic attribute information of the target object comprises a characteristic type, characteristic coordinates and a characteristic inspection area;
step S240: and marking the patrol target object set based on the target object characteristic attribute information to obtain the target patrol point set.
Specifically, the global inspection scene information is divided and marked, spatial modeling is firstly carried out based on the collected global inspection scene information, the scene data is modeled by utilizing a three-dimensional modeling technology, and an inspection scene three-dimensional model for obtaining the to-be-inspected scene is constructed. And the three-dimensional model of the inspection scene is divided into areas, so that the areas can be divided according to the scene function to generate a corresponding set of inspection scene dividing areas, such as an electric power equipment area, a machine room equipment area and the like. And then, respectively identifying patrol targets in the patrol scene segmented region sets, namely identifying and extracting targets such as required patrol equipment and channels in each region to obtain patrol target sets in each segmented region. And obtaining characteristic attribute information of the target object, wherein the characteristic attribute information of the target object is a classification attribute of the target object to be patrolled and comprises a characteristic type, a characteristic coordinate and a characteristic patrolling area of the target object, namely a patrol dividing area where the target object is located. And marking the patrol target object set based on the target object characteristic attribute information to obtain a target object set to be patrol after attribute marking, namely a target patrol point set. The attribute marking comprehensiveness of the object to be patrolled is improved, and the planning accuracy of the patrol path is further improved.
Step S300: performing path planning on the global inspection scene information based on the target inspection point set to obtain target inspection planning path information;
in one embodiment, the step S300 of the present application further includes:
step S310: performing route analysis based on the target routing inspection point set, and determining a routing inspection analysis route set;
step S320: constructing inspection valuation factors, wherein the inspection valuation factors comprise route length and inspection effect;
step S330: performing criticality distribution on the inspection valuation factors to obtain valuation factor criticality information;
step S340: constructing a patrol cost function according to the patrol valuation factors and the valuation factor criticality information;
step S350: and evaluating and screening the patrol analysis route set based on the patrol cost function to obtain the target patrol planning route information.
In one embodiment, the obtaining the model fusion parameters, step S350 of the present application further includes:
step S351: carrying out application function marking on each inspection point in the target inspection point set to obtain inspection point application function information;
step S352: carrying out emergency quantification based on the inspection point application function information, and determining an emergency coefficient of the inspection point;
step S353: carrying out inspection level division based on the inspection point urgency coefficient to obtain inspection point level information;
step S354: and obtaining the inspection frequency list information according to the inspection point level information, and determining the route inspection effect based on the inspection frequency list information.
Specifically, path planning is performed on the global inspection scene information based on the target inspection point set, and route analysis is performed on the basis of the target inspection point set, namely all routes passing through the target inspection point set are analyzed and integrated to obtain an inspection analysis route set. And constructing a patrol evaluation factor, wherein the patrol evaluation factor is an evaluation index for a patrol analysis route and comprises the length of the route and the patrol effect. The evaluation about the inspection effect is specifically to perform application function marking on each inspection point in the target inspection point set to obtain corresponding inspection point application function information. And carrying out urgency quantification based on the inspection point application function information, namely carrying out inspection importance analysis according to the application function, wherein the more important the application function is, the larger the corresponding inspection urgency coefficient is, the urgency is determined according to the actual application of the inspection scene according to the criterion, and the inspection point urgency coefficient is further analyzed. And carrying out inspection level division based on the inspection point urgency coefficient, namely carrying out inspection necessity degree division according to the urgency coefficient, wherein the higher the urgency coefficient is, the higher the corresponding inspection level is, so as to acquire inspection point level information. And obtaining the patrol frequency list information according to the patrol point level information, wherein the patrol frequency of the patrol frequency list information corresponds to the patrol point level. And based on the routing inspection frequency list information, conducting routing inspection frequency statistics on each routing inspection point on the routing inspection route, if the routing inspection frequency reaches the standard, the routing inspection effect is better, and if the routing inspection frequency does not reach the standard, the routing inspection effect is lost, so that the routing inspection effect is determined.
The inspection valuation factors are subjected to criticality distribution, namely the inspection valuation factors are subjected to weight distribution, and objective weight assignment can be performed through subjective weight assignment or according to inspection experienceThereby obtaining valuation factor criticality information. Constructing a patrol cost function according to the patrol valuation factors and the valuation factor criticality information, wherein the patrol cost function is specifically g=af 1 +bf 2 Wherein a is a route length weight, f 1 The route length evaluation information, b is the inspection effect weight, f 2 For evaluating information of inspection effect, the shorter the route is, f 1 The smaller the evaluation value is, the better the inspection effect is, f 2 The smaller the evaluation value. And carrying out evaluation screening on the patrol analysis route set based on the patrol cost function, namely inputting the evaluation value of each patrol analysis route into the patrol cost function to carry out cost result evaluation, obtaining the cost evaluation result of each route, and further selecting the route with the minimum substitution value as the target patrol planning path information. The method and the device realize rapid screening of the routing inspection planning path by using cost evaluation, and improve the routing inspection route planning accuracy and planning applicability.
Step S400: obtaining a patrol robot, wherein the patrol robot performs running patrol based on the target patrol planning path information to obtain a local patrol data stream;
step S500: the local inspection data stream and the target inspection planning path information are sent to a control console for analysis, and inspection optimization path information is output;
specifically, obtain the robot of patrolling and examining, the robot of patrolling and examining is the intelligent robot that is used for carrying out the scene and patrols and examine, is equipped with multiple functions such as image recognition, data record, transmission, intelligent warning, reduces the human input cost. The inspection robot performs running inspection based on the target inspection planning path information, and performs real-time monitoring integration on inspection path data and inspection result data, so that a local inspection data stream monitored by the robot is obtained, and the inspection data monitoring comprehensiveness is improved.
In one embodiment, the outputting the inspection optimization path information, step S600 of the present application further includes:
step S510: constructing a routing inspection path analysis model through the control console, wherein the routing inspection path analysis model comprises a routing inspection fault analysis model and a routing inspection obstacle avoidance analysis model;
step S520: analyzing the local inspection data stream based on the inspection fault analysis model and the inspection obstacle avoidance analysis model, and respectively outputting inspection fault analysis information and inspection obstacle avoidance analysis information;
step S530: determining the optimization parameters of the inspection route according to the inspection fault analysis information and the inspection obstacle avoidance analysis information;
step S540: and optimizing the target inspection planning path information based on the inspection route optimization parameters to obtain the inspection optimization path information.
Specifically, the local inspection data flow and the target inspection planning path information are sent to a control console for analysis, an inspection path analysis model is constructed through the control console, the inspection path analysis model is obtained through historical data training, and the method specifically comprises an inspection fault analysis model and an inspection obstacle avoidance analysis model, wherein the inspection fault analysis model is used for analyzing inspection point faults, and the obstacle avoidance parameter analysis is used for carrying out obstacle avoidance parameter analysis on obstacles appearing on an inspection path. And analyzing the local inspection data stream based on the inspection fault analysis model and the inspection obstacle avoidance analysis model, and respectively outputting inspection fault analysis information, namely fault information of an inspection point, and inspection obstacle avoidance analysis information, namely inspection obstacle avoidance analysis parameters. And re-planning a path according to the inspection fault analysis information and the inspection obstacle avoidance analysis information, wherein the inspection path obstacle avoidance is considered, the fault point equipment and the like are inspected again, and the optimization parameters of the inspection path are determined by re-planning, and the optimization parameters of the inspection path comprise an optimization angle, an optimization length and the like. And optimizing the target inspection planning path information based on the inspection route optimization parameters to obtain optimized and corrected inspection optimization path information. And the path optimization planning is carried out by combining global inspection and local inspection, so that the inspection path of the robot is corrected in real time, the comprehensiveness of path planning is realized, and the inspection effect and inspection efficiency of the robot are ensured.
Step S600: the inspection robot performs continuous inspection based on the inspection optimization path information to acquire inspection running track information;
in one embodiment, the step S600 of obtaining the information of the inspection moving track further includes:
step S610: the inspection robot performs continuous inspection based on the inspection optimization path information to acquire inspection path time sequence data;
step S620: selecting first time sequence inspection data information of the inspection path time sequence data, and performing drawing analysis based on the first time sequence inspection data information to generate a first time sequence inspection corner;
step S630: sequentially extracting the second time sequence inspection data information of the inspection path time sequence data to the Nth time sequence inspection data information according to the inspection time sequence to obtain second time sequence inspection corners to the Nth time sequence inspection corners;
step S640: and generating the inspection running track information based on the first time sequence inspection corner and the second time sequence inspection corner until the Nth time sequence inspection corner.
Specifically, the inspection robot performs continuous inspection based on the inspection optimization path information to obtain inspection path time sequence data, and the inspection path time sequence data are integrated and arranged according to the inspection time period sequence, wherein the time sequence length can be selected by itself, and the shorter the time sequence selection is, the higher the track analysis accuracy is. And selecting first time sequence inspection data information of the inspection path time sequence data, drawing and analyzing based on the first time sequence inspection data information, regarding the inspection robot as an inspection line, avoiding the loss of details drawn by an operating point, generating a first time sequence inspection corner according to the inspection direction of the robot, sequentially extracting N time sequence inspection data information from second time sequence inspection data information of the inspection path time sequence data to N time sequence inspection data information, and obtaining a corresponding second time sequence inspection corner to N time sequence inspection corner. And generating inspection running track information based on the first time sequence inspection corner and the second time sequence inspection corner to the Nth time sequence inspection corner, wherein the inspection running track information is the actual running track of the inspection robot. And the moving track is drawn through the time sequence inspection corner, so that the inspection track of the robot is visually displayed, and the control accuracy of the inspection track is improved.
Step S700: and comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation.
In one embodiment, the tracking control of the inspection robot is performed according to the inspection comparison deviation, and step S700 of the present application further includes:
step S710: determining an operation deviation correction parameter according to the inspection comparison deviation;
step S720: performing control precision analysis on the inspection robot to obtain a robot precision control threshold;
step S730: performing loss benefit analysis on the operation deviation correction parameters based on the robot precision control threshold value to generate a path compensation correction factor;
step S740: and carrying out path tracking compensation control on the inspection robot based on the path compensation correction factors.
Specifically, comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, namely actual inspection running deviation of the inspection robot. And tracking and controlling the inspection robot according to the inspection comparison deviation, and particularly determining an operation deviation correction parameter according to the inspection comparison deviation. And then, carrying out control precision analysis on the inspection robot, and determining a robot precision control threshold along with the use time length and the control inherent deviation of the robot, wherein the robot precision control threshold is the actual control deviation range of the robot. And carrying out loss benefit analysis on the operation deviation correction parameters based on the robot precision control threshold, namely calculating the deviation correction parameters according to the precision control threshold, and if the control threshold is an advance, carrying out loss subtraction on the corresponding advance of the deviation correction parameters to generate calculated path compensation correction factors. And carrying out path tracking compensation control on the inspection robot based on the path compensation correction factors, namely carrying out control parameter compensation on the inspection path, realizing adjustment and tracking on the inspection optimized path information, and further ensuring the control accuracy and the inspection effect of the inspection robot.
In one embodiment, as shown in fig. 3, a robotic inspection control system is provided, comprising: the system comprises a patrol scene acquisition module 11, a scene division marking module 12, a path planning module 13, a patrol data stream acquisition module 14, a data stream analysis module 15, a patrol running track acquisition module 16 and a tracking control module 17, wherein:
the inspection scene acquisition module 11 is used for acquiring global inspection scene information through monitoring of industrial visual equipment;
the scene division marking module 12 is used for dividing and marking the global inspection scene information to obtain a target inspection point set;
the path planning module 13 is configured to perform path planning on the global routing inspection scene information based on the target routing inspection point set, so as to obtain target routing inspection planning path information;
a patrol data stream obtaining module 14, configured to obtain a patrol robot, where the patrol robot performs running patrol based on the target patrol planning path information, and obtain a local patrol data stream;
the data flow analysis module 15 is configured to send the local inspection data flow and the target inspection planning path information to a console for analysis, and output inspection optimization path information;
the inspection running track acquisition module 16 is used for the inspection robot to perform continuous inspection based on the inspection optimization path information to acquire inspection running track information;
and the tracking control module 17 is used for comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation.
In one embodiment, the system further comprises:
the space modeling dividing unit is used for carrying out space modeling based on the global inspection scene information to obtain an inspection scene three-dimensional model, and carrying out region division on the inspection scene three-dimensional model to generate an inspection scene segmentation region set;
the patrol target object recognition unit is used for recognizing patrol target objects respectively on the patrol scene segmentation area set to obtain a patrol target object set;
the characteristic attribute acquisition unit is used for acquiring characteristic attribute information of a target object, wherein the characteristic attribute information of the target object comprises a characteristic type, characteristic coordinates and a characteristic inspection area;
and the target object marking unit is used for marking the patrol target object set based on the target object characteristic attribute information to obtain the target patrol point set.
In one embodiment, the system further comprises:
the routing inspection route analysis unit is used for carrying out route analysis based on the target routing inspection point set and determining a routing inspection analysis route set;
the inspection evaluation factor construction unit is used for constructing inspection evaluation factors, wherein the inspection evaluation factors comprise route length and inspection effect;
the criticality distribution unit is used for distributing criticality of the inspection valuation factors to obtain valuation factor criticality information;
the inspection cost function construction unit is used for constructing an inspection cost function according to the inspection valuation factors and the valuation factor criticality information;
and the route evaluation and screening unit is used for evaluating and screening the inspection analysis route set based on the inspection cost function to obtain the target inspection planning path information.
In one embodiment, the system further comprises:
the application function marking unit is used for marking the application function of each inspection point in the target inspection point set to obtain inspection point application function information;
the emergency quantification unit is used for quantifying the emergency based on the inspection point application function information and determining an emergency coefficient of the inspection point;
the inspection level dividing unit is used for carrying out inspection level division based on the inspection point urgency coefficient to obtain inspection point level information;
and the route inspection effect determining unit is used for obtaining inspection frequency list information according to the inspection point level information and determining the route inspection effect based on the inspection frequency list information.
In one embodiment, the system further comprises:
the path analysis model construction unit is used for constructing a routing inspection path analysis model through the control console, wherein the routing inspection path analysis model comprises a routing inspection fault analysis model and a routing inspection obstacle avoidance analysis model;
the data flow analysis unit is used for analyzing the local inspection data flow based on the inspection fault analysis model and the inspection obstacle avoidance analysis model and outputting inspection fault analysis information and inspection obstacle avoidance analysis information respectively;
the route optimization parameter determining unit is used for determining routing inspection route optimization parameters according to the routing inspection fault analysis information and the routing inspection obstacle avoidance analysis information;
and the planned path optimizing unit is used for optimizing the target inspection planned path information based on the inspection route optimizing parameters to obtain the inspection optimized path information.
In one embodiment, the system further comprises:
the path continuous inspection unit is used for the inspection robot to perform continuous inspection based on the inspection optimization path information to acquire inspection path time sequence data;
the data drawing and analyzing unit is used for selecting first time sequence inspection data information of the inspection path time sequence data, drawing and analyzing the first time sequence inspection data information to generate a first time sequence inspection corner;
the time sequence inspection corner obtaining unit is used for sequentially extracting the second time sequence inspection data information of the inspection path time sequence data to the Nth time sequence inspection data information according to the inspection time sequence to obtain the second time sequence inspection corner to the Nth time sequence inspection corner;
and the inspection running track generation unit is used for generating the inspection running track information based on the first time sequence inspection corner and the second time sequence inspection corner until the Nth time sequence inspection corner.
In one embodiment, the system further comprises:
the deviation correction parameter determining unit is used for determining an operation deviation correction parameter according to the inspection comparison deviation;
the control precision analysis unit is used for carrying out control precision analysis on the inspection robot to obtain a robot precision control threshold;
the parameter damage analysis unit is used for carrying out damage analysis on the operation deviation correction parameters based on the robot precision control threshold value to generate a path compensation correction factor;
and the tracking compensation control unit is used for carrying out path tracking compensation control on the inspection robot based on the path compensation correction factor.
For a specific embodiment of a robot inspection control system, reference may be made to the above embodiment of a robot inspection control method, which is not described herein. The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (5)
1. A method for controlling inspection of a robot, the method comprising:
monitoring and acquiring global inspection scene information through industrial visual equipment;
dividing and marking the global inspection scene information to obtain a target inspection point set;
performing path planning on the global inspection scene information based on the target inspection point set to obtain target inspection planning path information;
obtaining a patrol robot, wherein the patrol robot performs running patrol based on the target patrol planning path information to obtain a local patrol data stream;
the local inspection data stream and the target inspection planning path information are sent to a control console for analysis, and inspection optimization path information is output;
the inspection robot performs continuous inspection based on the inspection optimization path information to acquire inspection running track information;
comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation;
the obtaining the target patrol planning path information comprises the following steps:
performing route analysis based on the target routing inspection point set, and determining a routing inspection analysis route set;
constructing inspection valuation factors, wherein the inspection valuation factors comprise route length and inspection effect;
performing criticality distribution on the inspection valuation factors to obtain valuation factor criticality information;
constructing a patrol cost function according to the patrol valuation factors and the valuation factor criticality information;
evaluating and screening the patrol analysis route set based on the patrol cost function to obtain the target patrol planning route information;
the method comprises the following steps:
carrying out application function marking on each inspection point in the target inspection point set to obtain inspection point application function information;
carrying out emergency quantification based on the inspection point application function information, and determining an emergency coefficient of the inspection point;
carrying out inspection level division based on the inspection point urgency coefficient to obtain inspection point level information;
acquiring routing inspection frequency list information according to the routing inspection point level information, and determining a route routing inspection effect based on the routing inspection frequency list information;
the obtaining the inspection running track information comprises the following steps:
the inspection robot performs continuous inspection based on the inspection optimization path information to acquire inspection path time sequence data;
selecting first time sequence inspection data information of the inspection path time sequence data, and performing drawing analysis based on the first time sequence inspection data information to generate a first time sequence inspection corner;
sequentially extracting the second time sequence inspection data information of the inspection path time sequence data to the Nth time sequence inspection data information according to the inspection time sequence to obtain second time sequence inspection corners to the Nth time sequence inspection corners;
and generating the inspection running track information based on the first time sequence inspection corner and the second time sequence inspection corner until the Nth time sequence inspection corner.
2. The method of claim 1, wherein the obtaining the set of target inspection points comprises:
performing space modeling based on the global inspection scene information to obtain an inspection scene three-dimensional model, and performing region division on the inspection scene three-dimensional model to generate an inspection scene segmentation region set;
respectively identifying patrol targets in the patrol scene segmentation area set to obtain a patrol target set;
acquiring characteristic attribute information of a target object, wherein the characteristic attribute information of the target object comprises a characteristic type, characteristic coordinates and a characteristic inspection area;
and marking the patrol target object set based on the target object characteristic attribute information to obtain the target patrol point set.
3. The method of claim 1, wherein outputting the patrol optimization path information comprises:
constructing a routing inspection path analysis model through the control console, wherein the routing inspection path analysis model comprises a routing inspection fault analysis model and a routing inspection obstacle avoidance analysis model;
analyzing the local inspection data stream based on the inspection fault analysis model and the inspection obstacle avoidance analysis model, and respectively outputting inspection fault analysis information and inspection obstacle avoidance analysis information;
determining the optimization parameters of the inspection route according to the inspection fault analysis information and the inspection obstacle avoidance analysis information;
and optimizing the target inspection planning path information based on the inspection route optimization parameters to obtain the inspection optimization path information.
4. The method of claim 1, wherein tracking the inspection robot according to the inspection comparison deviation comprises:
determining an operation deviation correction parameter according to the inspection comparison deviation;
performing control precision analysis on the inspection robot to obtain a robot precision control threshold;
performing loss benefit analysis on the operation deviation correction parameters based on the robot precision control threshold value to generate a path compensation correction factor;
and carrying out path tracking compensation control on the inspection robot based on the path compensation correction factors.
5. A robotic inspection control system for performing the method of any one of claims 1-4, the system comprising:
the inspection scene acquisition module is used for acquiring global inspection scene information through monitoring of industrial visual equipment;
the scene division marking module is used for dividing and marking the global inspection scene information to obtain a target inspection point set;
the path planning module is used for carrying out path planning on the global inspection scene information based on the target inspection point set to obtain target inspection planning path information;
the inspection data stream obtaining module is used for obtaining an inspection robot, and the inspection robot performs operation inspection based on the target inspection planning path information to obtain a local inspection data stream;
the data flow analysis module is used for sending the local inspection data flow and the target inspection planning path information to a control console for analysis and outputting inspection optimization path information;
the inspection running track acquisition module is used for continuously inspecting the inspection robot based on the inspection optimization path information to acquire inspection running track information;
and the tracking control module is used for comparing and analyzing based on the inspection running track information and the inspection optimizing path information to obtain inspection comparison deviation, and tracking and controlling the inspection robot according to the inspection comparison deviation.
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