CN115640924B - Intelligent dispatching management method and system for inspection robot - Google Patents
Intelligent dispatching management method and system for inspection robot Download PDFInfo
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Abstract
The invention discloses an intelligent scheduling management method and system for a patrol robot, and relates to the field of patrol robot management, wherein the method comprises the following steps: acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots according to the basic parameter set to obtain target inspection robots; obtaining an inspection area allocation result; obtaining an allocation result of the target inspection robot; obtaining target inspection parameter information through an inspection parameter setting model; carrying out inspection by combining the distribution result of the target inspection robot to obtain inspection data; carrying out inspection risk evaluation on the data to obtain inspection risk data; obtaining inspection scheduling parameters through an inspection scheduling management model; and scheduling and managing the target inspection robot according to the target inspection robot. The method and the device have the advantages that the accuracy of scheduling management of the inspection robot is improved, and therefore the inspection quality of the inspection robot is improved.
Description
Technical Field
The invention relates to the field of inspection robot management, in particular to an intelligent dispatching management method and system for an inspection robot.
Background
The traditional inspection method relies on manual sense and experience, and is assisted by partial detection instruments, so that the defects of excessive subjective factors, high labor intensity, low automation degree, uneven inspection quality and the like exist. The appearance of the inspection robot well solves a plurality of problems existing in the traditional manual inspection, and the inspection robot is widely applied to the fields of substation inspection and the like. When the inspection robot performs inspection, the dispatching management of the inspection robot is an important means for ensuring the normal work of the inspection robot.
In the prior art, the scheduling management accuracy of the inspection robot is insufficient, so that the technical problem of poor inspection effect of the inspection robot is caused.
Disclosure of Invention
The application provides an intelligent dispatching management method and system for a patrol robot. The technical problems that in the prior art, the scheduling management accuracy aiming at the inspection robot is insufficient, and the inspection effect of the inspection robot is poor are solved.
In view of the above problems, the application provides an intelligent scheduling management method and system for a patrol robot.
In a first aspect, the present application provides an intelligent scheduling management method for a patrol robot, where the method is applied to an intelligent scheduling management system for a patrol robot, and the method includes: acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to obtain target inspection robots; performing inspection area allocation based on the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot based on the inspection area allocation result to obtain an allocation result of the target inspection robot; obtaining target inspection parameter information through an inspection parameter setting model based on an allocation result of the target inspection robot; based on the distribution result of the target inspection robot and the target inspection parameter information, the inspection is performed by the target inspection robot, so as to obtain inspection data; performing inspection risk evaluation based on the inspection data to obtain inspection risk data; based on the inspection risk data, obtaining inspection dispatching parameters through an inspection dispatching management model; and carrying out scheduling management on the target inspection robot based on the inspection scheduling parameters.
In a second aspect, the application further provides an intelligent scheduling management system of the inspection robot, wherein the system comprises: the screening module is used for acquiring basic parameter information of the target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to acquire the target inspection robots; the distribution module is used for carrying out patrol area distribution based on the basic parameter set of the target patrol area to obtain patrol area distribution results, and carrying out distribution of the target patrol robot based on the patrol area distribution results to obtain distribution results of the target patrol robot; the parameter setting module is used for obtaining target inspection parameter information through an inspection parameter setting model based on the distribution result of the target inspection robot; the inspection module is used for performing inspection through the target inspection robot based on the distribution result of the target inspection robot and the target inspection parameter information to obtain inspection data; the inspection risk evaluation module is used for performing inspection risk evaluation based on the inspection data to obtain inspection risk data; the inspection scheduling parameter determining module is used for obtaining inspection scheduling parameters through an inspection scheduling management model based on the inspection risk data; and the scheduling management module is used for scheduling and managing the target inspection robot based on the inspection scheduling parameters.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots according to the basic parameter set to acquire the target inspection robots; performing inspection area allocation according to the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot according to the inspection area allocation result to obtain an allocation result of the target inspection robot; based on the target inspection parameter information is obtained through an inspection parameter setting model; carrying out inspection by combining the distribution result of the target inspection robot to obtain inspection data; obtaining inspection risk data by performing inspection risk evaluation on the inspection data; based on the above, the inspection scheduling parameters are obtained through the inspection scheduling management model, and the target inspection robot is scheduled and managed according to the inspection scheduling parameters. The accuracy and the comprehensiveness of scheduling management of the inspection robot are improved, and the scheduling management effect of the inspection robot is improved, so that the inspection quality of the inspection robot is improved; meanwhile, the intelligent and scientific dispatching management process of the inspection robot is promoted, and a basic technical effect is laid for further wide application of the inspection robot.
Drawings
FIG. 1 is a flow chart of an intelligent dispatching management method of a patrol robot;
fig. 2 is a schematic flow chart of acquiring inspection risk data in the intelligent dispatching management method of the inspection robot;
FIG. 3 is a schematic flow chart of performing optimal scheduling management on a target inspection robot in the intelligent scheduling management method of the inspection robot;
fig. 4 is a schematic structural diagram of an intelligent dispatching management system of a patrol robot.
Reference numerals illustrate: the system comprises a screening module 11, an allocation module 12, a parameter setting module 13, a patrol module 14, a patrol risk evaluation module 15, a patrol scheduling parameter determining module 16 and a scheduling management module 17.
Detailed Description
The application provides an intelligent dispatching management method and system for a patrol robot. The technical problems that in the prior art, the scheduling management accuracy aiming at the inspection robot is insufficient, and the inspection effect of the inspection robot is poor are solved. The accuracy and the comprehensiveness of scheduling management of the inspection robot are improved, and the scheduling management effect of the inspection robot is improved, so that the inspection quality of the inspection robot is improved; meanwhile, the intelligent and scientific dispatching management process of the inspection robot is promoted, and a basic technical effect is laid for further wide application of the inspection robot.
Example 1
Referring to fig. 1, the application provides an intelligent scheduling management method for a patrol robot, wherein the method is applied to an intelligent scheduling management system for the patrol robot, and the method specifically comprises the following steps:
step S100: acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to obtain target inspection robots;
further, the step S100 of the present application further includes:
step S110: constructing an inspection area evaluation feature set;
step S120: performing feature recognition on a basic parameter set of the target inspection area based on the inspection area evaluation feature set to obtain a basic parameter feature recognition result;
step S130: collecting basic parameters of a plurality of inspection robots, and obtaining a basic parameter set of the inspection robots;
step S140: screening the basic parameter set of the inspection robot based on the basic parameter characteristic identification result to obtain screening data of the inspection robot;
step S150: and matching the plurality of inspection robots based on the screening data of the inspection robots to obtain the target inspection robot.
Specifically, the intelligent scheduling management system of the inspection robot collects basic parameter information of a target inspection area to obtain a basic parameter set of the target inspection area. And further, carrying out feature recognition on the basic parameter set of the target inspection area according to the inspection area evaluation feature set to obtain a basic parameter feature recognition result. Furthermore, the intelligent scheduling management system of the inspection robot collects basic parameters of a plurality of inspection robots to obtain a basic parameter set of the inspection robots. And then, screening the basic parameter set of the inspection robot according to the basic parameter characteristic identification result to obtain screening data of the inspection robot, and matching a plurality of inspection robots according to the screening data to determine a target inspection robot.
The target inspection area can be any area for intelligent inspection by using the intelligent dispatching management system of the inspection robot. For example, the target patrol area may be a place such as a mall, a residential area, an office park, or the like. The basic parameter set of the target inspection area comprises data information such as the area, the structural composition, the environmental parameters, the inspection working range and the like of the target inspection area. The inspection area evaluation feature set comprises a plurality of inspection area evaluation features preset by the intelligent dispatching management system of the inspection robot. For example, the inspection area evaluation feature set includes data information such as an environmental temperature, an environmental humidity, an inspection work requirement and the like of the inspection area. And the basic parameter characteristic identification result comprises data information corresponding to the inspection area evaluation characteristic set in the basic parameter set of the target inspection area. The basic parameter set of the inspection robot comprises the type, the size, the weight, the working environment temperature, the working environment humidity, the inspection working characteristics of a plurality of inspection robots, and working parameter information such as power, turning radius, climbing range and the like. The plurality of inspection robots comprise crawler-type inspection robots, wheel-type inspection robots, track-type inspection robots and other types of inspection robots. The screening data of the inspection robot comprise data information corresponding to the basic parameter characteristic identification result in a basic parameter set of the inspection robot. The target inspection robot is one of a plurality of inspection robots, and corresponds to screening data of the inspection robots. The method and the device have the advantages that basic parameter information of the target inspection area is determined, a plurality of inspection robots are screened according to the basic parameter information, the target inspection robot which is relatively matched with the target inspection area is determined, and a foundation is laid for subsequent scheduling management of the target inspection robot.
Step S200: performing inspection area allocation based on the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot based on the inspection area allocation result to obtain an allocation result of the target inspection robot;
further, step S200 of the present application further includes:
step S210: obtaining structural feature parameters based on the basic parameter set of the target inspection area;
step S220: dividing a target inspection area based on the structural characteristic parameters to obtain an inspection area dividing result;
specifically, the structural characteristic parameters are extracted from the basic parameter set of the target inspection area, the target inspection area is divided according to the structural characteristic parameters, and the inspection area division result is determined. The structural characteristic parameters comprise data information such as the area, the position, the layout planning, the live-action map and the like of the target inspection area. The inspection area dividing result comprises specific inspection area data information obtained by dividing the target inspection area according to the structural characteristic parameters. For example, the target patrol area is a residential area. The structural characteristic parameters comprise data information such as the number of residential buildings in a residential building, the distance between the residential buildings, the external structural parameters of the residential buildings, the internal structural parameters of the residential buildings, the structural parameters of parking lots and the like. The patrol area division result comprises a residential building area, a parking area, a resident activity area, a resident service area and the like. The technical effects of reasonably dividing the target inspection area according to the structural characteristic parameters, obtaining the inspection area dividing result and tamping the foundation for obtaining the inspection area distribution result later are achieved.
Step S230: performing routing inspection route distribution based on the routing inspection area division result to obtain a routing inspection route distribution result;
further, step S230 of the present application further includes:
step S231: historical inspection information acquisition is carried out based on the inspection area division result, and area historical inspection information is obtained;
step S232: performing regional inspection grade assessment based on the regional historical inspection information to obtain a regional inspection grade assessment result;
step S233: acquiring historical patrol route information based on the regional historical patrol information;
step S234: matching the regional inspection grade assessment result based on the historical inspection route information to obtain regional inspection characteristic information;
step S235: and carrying out routing inspection route distribution on the routing inspection regional division result based on the regional routing inspection characteristic information to obtain the routing inspection route distribution result.
Step S240: and obtaining the routing inspection area distribution result based on the routing inspection area division result and the routing inspection route distribution result.
Specifically, the intelligent scheduling management system of the inspection robot collects historical inspection information of the target inspection area according to the inspection area dividing result to obtain area historical inspection information, evaluates the area inspection grade according to the inspection area dividing result, and obtains an area inspection grade evaluation result. Further, historical inspection route information is extracted from the obtained regional historical inspection information, and is matched with a regional inspection grade assessment result to obtain regional inspection characteristic information. And further, carrying out routing inspection route distribution on the routing inspection area division result according to the area routing inspection characteristic information to obtain routing inspection route distribution results, and determining the routing inspection area distribution results by combining the routing inspection area division results. And then, distributing the target inspection robots according to the inspection area distribution result to obtain the distribution result of the target inspection robots.
The regional historical inspection information comprises data information such as historical inspection route information, historical inspection frequency information, historical inspection time, historical inspection results and the like corresponding to the inspection regional division results. The regional inspection grade assessment result comprises inspection grade information corresponding to the inspection regional division result. For example, the patrol area division result includes an area a. In the regional historical inspection information, the historical inspection routes corresponding to the region A are more, the historical inspection frequency is higher, and the historical inspection results show that the inspection of the region A is abnormal, so that the region A has higher inspection grade in the obtained regional inspection grade evaluation result. The historical inspection route information comprises a plurality of historical inspection routes corresponding to the inspection area division results. The regional inspection characteristic information comprises regional inspection grade assessment results and historical inspection route information corresponding to the regional inspection grade assessment results. And the routing inspection route distribution result comprises routing inspection route distribution of the routing inspection area division result according to the area routing inspection characteristic information, and the routing inspection route corresponding to the routing inspection area division result is obtained. For example, when the regional inspection feature information indicates that the region B has a higher inspection level, the historical inspection route information corresponding to the region B may be refined, and then the inspection route corresponding to the region B may be obtained. When the regional inspection characteristic information indicates that the region C has a lower inspection grade, the historical inspection route information corresponding to the region C can be directly set as an inspection route corresponding to the region C. The routing inspection area distribution result comprises a routing inspection area division result and a routing inspection route distribution result. The allocation results of the target inspection robots comprise the number of the target inspection robots, and inspection area division results and inspection route allocation results corresponding to each target inspection robot. For example, when the inspection area allocation result indicates that the area D has a plurality of inspection routes, the obtained allocation result of the target inspection robot has a plurality of target inspection robots in the area D. The method and the device have the advantages that the routing distribution is carried out on the target routing area according to the routing area dividing result, the accurate and reliable routing distribution result is obtained, the target routing robot is reasonably distributed according to the routing distribution result, the accurate distribution result of the target routing robot is obtained, and the accuracy of the follow-up scheduling management of the target routing robot is improved.
Step S300: obtaining target inspection parameter information through an inspection parameter setting model based on an allocation result of the target inspection robot;
step S400: based on the distribution result of the target inspection robot and the target inspection parameter information, the inspection is performed by the target inspection robot, so as to obtain inspection data;
specifically, the obtained distribution result of the target inspection robot is used as input information, an inspection parameter setting model is input, and target inspection parameter information is obtained. And then, the target inspection robot performs inspection according to the distribution result of the target inspection robot and the target inspection parameter information to obtain inspection data. The inspection parameter setting model is obtained through training of a large amount of data information related to the distribution result of the inspection robot, and has the functions of performing intelligent inspection parameter matching on the input distribution result of the target inspection robot. The target inspection parameter information comprises inspection time, inspection task, inspection frequency and the like corresponding to the allocation result of the target inspection robot. The inspection data comprise data information such as inspection environment, inspection condition and the like obtained when the target inspection robot inspects according to the distribution result of the target inspection robot and the target inspection parameter information. Illustratively, the target patrol area is a residential area. And the allocation result of the target inspection robot is that the target inspection robot E performs inspection of the F inspection route at the entrance and exit of the residential area. The target inspection parameter information comprises the inspection time G and the inspection frequency H of the target inspection robot, and the inspection tasks of the target inspection robot are face recognition, resident household judgment, body temperature detection, external visitor registration and the like of the entering and exiting personnel. The inspection data comprise face recognition results of the people entering and exiting, body temperature detection data, whether the people entering and exiting are resident households, inspection weather corresponding to the inspection time and other data information. The technical effects of obtaining scientific and reasonable target inspection parameter information through the inspection parameter setting model, carrying out inspection by combining an allocation result of the target inspection robot, obtaining inspection data and providing reliable data support for subsequently obtaining inspection risk data are achieved.
Step S500: performing inspection risk evaluation based on the inspection data to obtain inspection risk data;
further, as shown in fig. 3, step S500 of the present application further includes:
step S510: constructing a patrol risk characteristic evaluation set, wherein the patrol risk characteristic evaluation set comprises a plurality of patrol risk characteristics and a plurality of patrol risk characteristic evaluation values;
step S520: performing inspection risk evaluation on the inspection data based on the inspection risk feature evaluation set to obtain an inspection risk evaluation result;
step S530: and obtaining the inspection risk data based on the inspection risk evaluation result.
Specifically, the intelligent scheduling management system of the inspection robot obtains an inspection risk characteristic evaluation set through big data query. Further, carrying out inspection risk evaluation on the obtained inspection data according to the inspection risk characteristic evaluation set to obtain an inspection risk evaluation result, and determining the inspection risk data according to the inspection risk evaluation result. The inspection risk feature evaluation set comprises a plurality of inspection risk features and a plurality of inspection risk feature evaluation values. And the plurality of inspection risk characteristics and the plurality of inspection risk characteristic evaluation values have a corresponding relationship. The inspection risk evaluation result comprises inspection risk characteristics corresponding to the inspection data and inspection risk characteristic evaluation values. The inspection data includes body temperature detection data of an entrance and an exit of a certain station, portable object detection data, inspection time, inspection weather and other data information. The inspection risk characteristic evaluation set comprises abnormal body temperature inspection risk characteristics and abnormal article inspection risk characteristics, and inspection risk characteristic evaluation values corresponding to the abnormal body temperature inspection risk characteristics and the abnormal article inspection risk characteristics are a and b respectively. When the body temperature detection data in the inspection data does not meet the normal body temperature of the human body, the obtained inspection risk evaluation result comprises the body temperature detection data, abnormal body temperature inspection risk characteristics and inspection risk characteristic evaluation value a. When the portable article detection data in the inspection data indicate that dangerous articles such as fireworks and crackers are carried by in-out personnel, the obtained inspection risk evaluation result comprises the portable article detection data, abnormal article inspection risk characteristics and inspection risk characteristic evaluation values b. The inspection risk data comprises inspection risk evaluation results, and data information such as a target inspection robot, an inspection area dividing result, an inspection route distribution result and the like corresponding to the inspection risk evaluation results. The technical effects of carrying out inspection risk evaluation on inspection data through the inspection risk characteristic evaluation set and obtaining the inspection risk data are achieved, and therefore the accuracy of the follow-up scheduling management of the target inspection robot is improved.
Further, after step S530 of the present application, the method further includes:
step S540: carrying out inspection obstacle recognition based on the inspection data to obtain an inspection obstacle recognition result;
step S550: performing inspection risk evaluation on the inspection obstacle recognition result to obtain an inspection obstacle risk evaluation coefficient;
step S560: obtaining a risk evaluation coefficient threshold value;
step S570: judging whether the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold;
step S580: and if the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold, adding the patrol obstacle recognition result to the patrol risk data.
Specifically, the obtained inspection data is subjected to inspection obstacle recognition, an inspection obstacle recognition result is obtained, inspection risk evaluation is performed on the inspection obstacle recognition result, and an inspection obstacle risk evaluation coefficient is obtained. Further, whether the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold value is judged, and when the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold value, the patrol obstacle recognition result is added to the patrol risk data. The inspection obstacle recognition result comprises the type, speed and distance of the inspection obstacle, the inspection area division result corresponding to the inspection obstacle, the inspection route distribution result and other data information. The inspection obstacle risk evaluation coefficient is parameter information for representing inspection risks corresponding to the inspection obstacle identification result. For example, when the inspection data indicates that a child runs to a target inspection robot that is performing inspection work, the inspection obstacle recognition result includes a running speed, an inspection area division result, an inspection route allocation result, and a distance between the child and the target inspection robot, which correspond to the child. The greater the running speed of the child, the smaller the distance between the child and the target inspection robot, and the greater the corresponding inspection obstacle risk evaluation coefficient. And the risk evaluation coefficient threshold value is determined by custom setting of the intelligent scheduling management system of the inspection robot. The inspection risk data further comprises inspection obstacle recognition results corresponding to the inspection obstacle risk evaluation coefficients meeting the risk evaluation coefficient threshold. The method and the device achieve the technical effects that reliable patrol obstacle risk evaluation coefficients are obtained through patrol obstacle recognition and patrol risk evaluation, the reliable patrol obstacle risk evaluation coefficients are compared with risk evaluation coefficient thresholds, patrol obstacle recognition results corresponding to the patrol obstacle risk evaluation coefficients meeting the risk evaluation coefficient thresholds are added to patrol risk data, the comprehensiveness of the patrol risk data is improved, and therefore accuracy of scheduling management of a target patrol robot is improved.
Step S600: based on the inspection risk data, obtaining inspection dispatching parameters through an inspection dispatching management model;
step S700: and carrying out scheduling management on the target inspection robot based on the inspection scheduling parameters.
Specifically, the inspection risk data is used as input information, an inspection dispatching management model is input, inspection dispatching parameters are obtained, and dispatching management is carried out on the target inspection robot according to the inspection dispatching parameters. The inspection scheduling management model is obtained through training of a large amount of data information related to inspection risk data, and has the functions of intelligent analysis, inspection scheduling parameter matching and the like of the input inspection risk data. The routing inspection scheduling parameters comprise routing inspection route adjustment for routing inspection route distribution results, adjustment for inspection time and inspection frequency, redistribution for target inspection robots and the like. Illustratively, when the inspection risk data indicates that the Y area has an inspection risk evaluation result, the obtained inspection scheduling parameters include allocation of more target inspection robots to the Y area, refinement of an inspection route, and adjustment of an inspection frequency to the target inspection robots of the Y area. The technical effects that the inspection risk data is analyzed through the inspection dispatching management model, reasonable and reliable inspection dispatching parameters are obtained, the target inspection robot is accurately dispatched and managed according to the inspection dispatching parameters, and the inspection quality of the target inspection robot is improved are achieved.
Further, as shown in fig. 4, after step S700 of the present application, the method further includes:
step S810: performing scheduling management effect evaluation on the routing inspection scheduling parameters to obtain routing inspection scheduling evaluation coefficients;
step S820: obtaining a patrol scheduling evaluation coefficient threshold value;
step S830: judging whether the inspection scheduling evaluation coefficient meets the inspection scheduling evaluation coefficient threshold;
step S840: and if the inspection dispatching evaluation coefficient does not meet the inspection dispatching evaluation coefficient threshold, obtaining a dispatching management early-warning instruction, and carrying out optimized dispatching management on the target inspection robot based on the dispatching management early-warning instruction.
Specifically, when the target inspection robot is subjected to dispatching management according to the inspection dispatching parameters, the intelligent dispatching management system of the inspection robot is used for evaluating dispatching management effects of the inspection dispatching parameters, and an inspection dispatching evaluation coefficient is obtained. Further, whether the inspection dispatching evaluation coefficient meets the inspection dispatching evaluation coefficient threshold value is judged, and when the inspection dispatching evaluation coefficient does not meet the inspection dispatching evaluation coefficient threshold value, the intelligent dispatching management system of the inspection robot automatically acquires dispatching management early warning instructions and performs optimized dispatching management on the target inspection robot according to the dispatching management early warning instructions.
The inspection scheduling evaluation coefficient is parameter information used for representing the scheduling management effect of the inspection scheduling parameter. For example, if a certain inspection area still has more inspection risk evaluation results after the target inspection robot is subjected to the dispatching management according to the inspection dispatching parameters, the dispatching management effect of the inspection dispatching parameters is poor, and the corresponding inspection dispatching evaluation coefficients are low. The inspection dispatching evaluation coefficient threshold is determined by the intelligent dispatching management system of the inspection robot according to the accuracy requirement user-defined setting of dispatching management of the inspection robot. The scheduling management early warning instruction is instruction information used for representing that the routing inspection scheduling evaluation coefficient does not meet the routing inspection scheduling evaluation coefficient threshold value and needs to optimize routing inspection scheduling parameters corresponding to the routing inspection scheduling evaluation coefficient. The method includes the steps that after a dispatching management early warning instruction is obtained, the inspection dispatching management model can be trained and updated, optimized inspection dispatching parameters are obtained through the inspection dispatching management model after the training and updating, and the target inspection robot is optimized and dispatched according to the optimized inspection dispatching parameters. The method has the advantages that the dispatching management effect evaluation is carried out on the inspection dispatching parameters, when the inspection dispatching evaluation coefficient does not meet the inspection dispatching evaluation coefficient threshold, the target inspection robot is optimized to be dispatched and managed according to the dispatching management early-warning instruction, the dispatching management accuracy of the inspection robot is improved, and the technical effect of dispatching management quality of the inspection robot is improved.
In summary, the intelligent scheduling management method for the inspection robot provided by the application has the following technical effects:
1. acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots according to the basic parameter set to acquire the target inspection robots; performing inspection area allocation according to the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot according to the inspection area allocation result to obtain an allocation result of the target inspection robot; based on the target inspection parameter information is obtained through an inspection parameter setting model; carrying out inspection by combining the distribution result of the target inspection robot to obtain inspection data; obtaining inspection risk data by performing inspection risk evaluation on the inspection data; based on the above, the inspection scheduling parameters are obtained through the inspection scheduling management model, and the target inspection robot is scheduled and managed according to the inspection scheduling parameters. The accuracy and the comprehensiveness of scheduling management of the inspection robot are improved, and the scheduling management effect of the inspection robot is improved, so that the inspection quality of the inspection robot is improved; meanwhile, the intelligent and scientific dispatching management process of the inspection robot is promoted, and a basic technical effect is laid for further wide application of the inspection robot.
2. And carrying out routing inspection route distribution on the target routing inspection area according to the routing inspection area dividing result to obtain an accurate and reliable routing inspection route distribution result, and carrying out reasonable distribution on the target routing inspection robot according to the routing inspection route distribution result to obtain an accurate target routing inspection robot distribution result, thereby improving the accuracy of scheduling management on the target routing inspection robot.
3. By means of inspection obstacle recognition and inspection risk evaluation, a reliable inspection obstacle risk evaluation coefficient is obtained and compared with a risk evaluation coefficient threshold, inspection obstacle recognition results corresponding to the inspection obstacle risk evaluation coefficient meeting the risk evaluation coefficient threshold are added to inspection risk data, the comprehensiveness of the inspection risk data is improved, and therefore accuracy of scheduling management of a target inspection robot is improved.
Example two
Based on the same inventive concept as the intelligent scheduling management method of the inspection robot in the foregoing embodiment, the invention also provides an intelligent scheduling management system of the inspection robot, please refer to fig. 4, the system includes:
the screening module 11 is used for acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to obtain target inspection robots;
The distribution module 12 is used for carrying out patrol area distribution based on the basic parameter set of the target patrol area to obtain patrol area distribution results, and carrying out distribution of the target patrol robot based on the patrol area distribution results to obtain distribution results of the target patrol robot;
the parameter setting module 13 is used for obtaining target inspection parameter information through an inspection parameter setting model based on the distribution result of the target inspection robot;
the inspection module 14 is configured to perform inspection by using the target inspection robot based on the allocation result of the target inspection robot and the target inspection parameter information, so as to obtain inspection data;
the inspection risk evaluation module 15 is used for performing inspection risk evaluation based on the inspection data to obtain inspection risk data;
the inspection scheduling parameter determining module 16, wherein the inspection scheduling parameter determining module 16 is configured to obtain inspection scheduling parameters through an inspection scheduling management model based on the inspection risk data;
and the dispatching management module 17 is used for dispatching and managing the target inspection robot based on the inspection dispatching parameters by the dispatching management module 17.
Further, the system further comprises:
the inspection area evaluation feature construction module is used for constructing an inspection area evaluation feature set;
the basic parameter characteristic recognition result acquisition module is used for carrying out characteristic recognition on the basic parameter set of the target inspection area based on the inspection area evaluation characteristic set to acquire a basic parameter characteristic recognition result;
the inspection robot parameter acquisition module is used for acquiring basic parameters of a plurality of inspection robots and acquiring a basic parameter set of the inspection robots;
the screening data acquisition module is used for screening the basic parameter set of the inspection robot based on the basic parameter characteristic identification result to acquire screening data of the inspection robot;
and the target inspection robot determining module is used for matching the plurality of inspection robots based on the screening data of the inspection robots to obtain the target inspection robot.
Further, the system further comprises:
The structural feature parameter obtaining module is used for obtaining structural feature parameters based on the basic parameter set of the target inspection area;
the inspection area division result obtaining module is used for dividing a target inspection area based on the structural characteristic parameters to obtain an inspection area division result;
the routing inspection route distribution module is used for carrying out routing inspection route distribution based on the routing inspection area division result to obtain a routing inspection route distribution result;
and the patrol area allocation result determining module is used for obtaining the patrol area allocation result based on the patrol area division result and the patrol route allocation result.
Further, the system further comprises:
the historical inspection information acquisition module is used for acquiring historical inspection information based on the inspection area division result to obtain area historical inspection information;
the regional inspection grade assessment module is used for carrying out regional inspection grade assessment based on the regional historical inspection information to obtain regional inspection grade assessment results;
The historical inspection route information determining module is used for obtaining historical inspection route information based on the regional historical inspection information;
the regional inspection characteristic information determining module is used for matching the regional inspection grade assessment result based on the historical inspection route information to obtain regional inspection characteristic information;
and the routing inspection route distribution result obtaining module is used for carrying out routing inspection route distribution on the routing inspection area division result based on the area routing inspection characteristic information to obtain the routing inspection route distribution result.
Further, the system further comprises:
the inspection risk feature evaluation construction module is used for constructing an inspection risk feature evaluation set, wherein the inspection risk feature evaluation set comprises a plurality of inspection risk features and a plurality of inspection risk feature evaluation values;
the inspection risk evaluation result obtaining module is used for carrying out inspection risk evaluation on the inspection data based on the inspection risk characteristic evaluation set to obtain an inspection risk evaluation result;
And the inspection risk data acquisition module is used for acquiring the inspection risk data based on the inspection risk evaluation result.
Further, the system further comprises:
the inspection obstacle recognition module is used for carrying out inspection obstacle recognition based on the inspection data to obtain an inspection obstacle recognition result;
the inspection obstacle risk evaluation coefficient obtaining module is used for carrying out inspection risk evaluation on the inspection obstacle identification result to obtain an inspection obstacle risk evaluation coefficient;
the risk evaluation coefficient threshold determining module is used for obtaining a risk evaluation coefficient threshold;
the first judging module is used for judging whether the risk evaluation coefficient of the inspection obstacle meets the risk evaluation coefficient threshold value or not;
the first execution module is used for adding the inspection obstacle recognition result to the inspection risk data if the inspection obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold.
Further, the system further comprises:
The scheduling management effect evaluation module is used for performing scheduling management effect evaluation on the routing inspection scheduling parameters to obtain routing inspection scheduling evaluation coefficients;
the inspection scheduling evaluation coefficient threshold obtaining module is used for obtaining an inspection scheduling evaluation coefficient threshold;
the second judging module is used for judging whether the inspection scheduling evaluation coefficient meets the inspection scheduling evaluation coefficient threshold value or not;
and the optimized dispatching management module is used for obtaining dispatching management early warning instructions and carrying out optimized dispatching management on the target inspection robot based on the dispatching management early warning instructions if the inspection dispatching evaluation coefficient does not meet the inspection dispatching evaluation coefficient threshold.
The application provides an intelligent scheduling management method of a patrol robot, wherein the method is applied to an intelligent scheduling management system of the patrol robot, and the method comprises the following steps: acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots according to the basic parameter set to acquire the target inspection robots; performing inspection area allocation according to the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot according to the inspection area allocation result to obtain an allocation result of the target inspection robot; based on the target inspection parameter information is obtained through an inspection parameter setting model; carrying out inspection by combining the distribution result of the target inspection robot to obtain inspection data; obtaining inspection risk data by performing inspection risk evaluation on the inspection data; based on the above, the inspection scheduling parameters are obtained through the inspection scheduling management model, and the target inspection robot is scheduled and managed according to the inspection scheduling parameters. The technical problems that in the prior art, the scheduling management accuracy aiming at the inspection robot is insufficient, and the inspection effect of the inspection robot is poor are solved. The accuracy and the comprehensiveness of scheduling management of the inspection robot are improved, and the scheduling management effect of the inspection robot is improved, so that the inspection quality of the inspection robot is improved; meanwhile, the intelligent and scientific dispatching management process of the inspection robot is promoted, and a basic technical effect is laid for further wide application of the inspection robot.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The specification and drawings are merely exemplary of the present application, and the present application is intended to cover modifications and variations of the present application provided they come within the scope of the application and its equivalents.
Claims (4)
1. An intelligent scheduling management method for a patrol robot is characterized by comprising the following steps:
acquiring basic parameter information of a target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to obtain target inspection robots;
performing inspection area allocation based on the basic parameter set of the target inspection area to obtain an inspection area allocation result, and performing allocation of the target inspection robot based on the inspection area allocation result to obtain an allocation result of the target inspection robot;
obtaining target inspection parameter information through an inspection parameter setting model based on an allocation result of the target inspection robot;
Based on the distribution result of the target inspection robot and the target inspection parameter information, the inspection is performed by the target inspection robot, so as to obtain inspection data;
and carrying out inspection risk evaluation based on the inspection data to obtain inspection risk data, wherein the inspection risk data comprises: constructing a patrol risk characteristic evaluation set, wherein the patrol risk characteristic evaluation set comprises a plurality of patrol risk characteristics and a plurality of patrol risk characteristic evaluation values; performing inspection risk evaluation on the inspection data based on the inspection risk feature evaluation set to obtain an inspection risk evaluation result; acquiring the inspection risk data based on the inspection risk evaluation result; carrying out inspection obstacle recognition based on the inspection data to obtain an inspection obstacle recognition result; performing inspection risk evaluation on the inspection obstacle recognition result to obtain an inspection obstacle risk evaluation coefficient; obtaining a risk evaluation coefficient threshold value; judging whether the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold; if the patrol obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold, adding the patrol obstacle recognition result to the patrol risk data;
Based on the inspection risk data, obtaining inspection dispatching parameters through an inspection dispatching management model;
scheduling management is carried out on the target inspection robot based on the inspection scheduling parameters;
wherein, the method further comprises the steps of:
obtaining structural feature parameters based on the basic parameter set of the target inspection area;
dividing a target inspection area based on the structural characteristic parameters to obtain an inspection area dividing result;
performing routing inspection route distribution based on the routing inspection area division result to obtain a routing inspection route distribution result;
obtaining a routing inspection area distribution result based on the routing inspection area division result and the routing inspection route distribution result;
the method for obtaining the routing inspection route distribution result further comprises the following steps:
historical inspection information acquisition is carried out based on the inspection area division result, and area historical inspection information is obtained;
performing regional inspection grade assessment based on the regional historical inspection information to obtain a regional inspection grade assessment result;
acquiring historical patrol route information based on the regional historical patrol information;
matching the regional inspection grade assessment result based on the historical inspection route information to obtain regional inspection characteristic information;
And carrying out routing inspection route distribution on the routing inspection regional division result based on the regional routing inspection characteristic information to obtain the routing inspection route distribution result.
2. The method of claim 1, wherein the obtaining a target inspection robot, the method further comprising:
constructing an inspection area evaluation feature set;
performing feature recognition on a basic parameter set of the target inspection area based on the inspection area evaluation feature set to obtain a basic parameter feature recognition result;
collecting basic parameters of a plurality of inspection robots, and obtaining a basic parameter set of the inspection robots;
screening the basic parameter set of the inspection robot based on the basic parameter characteristic identification result to obtain screening data of the inspection robot;
and matching the plurality of inspection robots based on the screening data of the inspection robots to obtain the target inspection robot.
3. The method of claim 1, wherein the method further comprises:
performing scheduling management effect evaluation on the routing inspection scheduling parameters to obtain routing inspection scheduling evaluation coefficients;
obtaining a patrol scheduling evaluation coefficient threshold value;
judging whether the inspection scheduling evaluation coefficient meets the inspection scheduling evaluation coefficient threshold;
And if the inspection dispatching evaluation coefficient does not meet the inspection dispatching evaluation coefficient threshold, obtaining a dispatching management early-warning instruction, and carrying out optimized dispatching management on the target inspection robot based on the dispatching management early-warning instruction.
4. An intelligent scheduling management system for inspection robots, the system comprising:
the screening module is used for acquiring basic parameter information of the target inspection area, acquiring a basic parameter set of the target inspection area, and screening a plurality of inspection robots based on the basic parameter set of the target inspection area to acquire the target inspection robots;
the distribution module is used for carrying out patrol area distribution based on the basic parameter set of the target patrol area to obtain patrol area distribution results, and carrying out distribution of the target patrol robot based on the patrol area distribution results to obtain distribution results of the target patrol robot;
the parameter setting module is used for obtaining target inspection parameter information through an inspection parameter setting model based on the distribution result of the target inspection robot;
the inspection module is used for performing inspection through the target inspection robot based on the distribution result of the target inspection robot and the target inspection parameter information to obtain inspection data;
The inspection risk evaluation module is used for performing inspection risk evaluation based on the inspection data to obtain inspection risk data;
the inspection risk feature evaluation construction module is used for constructing an inspection risk feature evaluation set, wherein the inspection risk feature evaluation set comprises a plurality of inspection risk features and a plurality of inspection risk feature evaluation values;
the inspection risk evaluation result obtaining module is used for carrying out inspection risk evaluation on the inspection data based on the inspection risk characteristic evaluation set to obtain an inspection risk evaluation result;
the inspection risk data acquisition module is used for acquiring the inspection risk data based on the inspection risk evaluation result;
the inspection obstacle recognition module is used for carrying out inspection obstacle recognition based on the inspection data to obtain an inspection obstacle recognition result;
the inspection obstacle risk evaluation coefficient obtaining module is used for carrying out inspection risk evaluation on the inspection obstacle identification result to obtain an inspection obstacle risk evaluation coefficient;
The risk evaluation coefficient threshold determining module is used for obtaining a risk evaluation coefficient threshold;
the first judging module is used for judging whether the risk evaluation coefficient of the inspection obstacle meets the risk evaluation coefficient threshold value or not;
the first execution module is used for adding the inspection obstacle recognition result to the inspection risk data if the inspection obstacle risk evaluation coefficient meets the risk evaluation coefficient threshold;
the inspection scheduling parameter determining module is used for obtaining inspection scheduling parameters through an inspection scheduling management model based on the inspection risk data;
the scheduling management module is used for scheduling and managing the target inspection robot based on the inspection scheduling parameters;
the structural feature parameter obtaining module is used for obtaining structural feature parameters based on the basic parameter set of the target inspection area;
the inspection area division result obtaining module is used for dividing a target inspection area based on the structural characteristic parameters to obtain an inspection area division result;
The routing inspection route distribution module is used for carrying out routing inspection route distribution based on the routing inspection area division result to obtain a routing inspection route distribution result;
the inspection area distribution result determining module is used for obtaining the inspection area distribution result based on the inspection area division result and the inspection route distribution result;
the historical inspection information acquisition module is used for acquiring historical inspection information based on the inspection area division result to obtain area historical inspection information;
the regional inspection grade assessment module is used for carrying out regional inspection grade assessment based on the regional historical inspection information to obtain regional inspection grade assessment results;
the historical inspection route information determining module is used for obtaining historical inspection route information based on the regional historical inspection information;
the regional inspection characteristic information determining module is used for matching the regional inspection grade assessment result based on the historical inspection route information to obtain regional inspection characteristic information;
And the routing inspection route distribution result obtaining module is used for carrying out routing inspection route distribution on the routing inspection area division result based on the area routing inspection characteristic information to obtain the routing inspection route distribution result.
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