Inspection route planning method, device, electronic device and storage medium

Abstract

The present disclosure relates to a patrol path planning method, device, electronic device, and storage medium, and relates to the field of computer technology. The method obtains resource-related information of multiple resources to be patrolled and subject-related information of patrol subjects indicated by the route planning operation in response to the route planning operation; inputs the resource-related information and subject-related information into a target route planning model to generate a selected patrol path for the multiple resources to be patrolled based on the resource-related information and subject-related information; obtains the cumulative patrol time required to patrol the multiple resources to be patrolled using the selected patrol path; and when the difference between the cumulative patrol time and the remaining patrol time of the patrol subject meets a preset requirement, determines the selected patrol path as the target patrol path. In this way, a patrol path can be automatically generated for the resources to be patrolled based on the relevant information of the resources to be patrolled and the patrol subject, eliminating the need for manual route planning.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a patrol route planning method, device, electronic device, and storage medium. Background Art

[0002] Currently, most industries require regular inspections of their resources (e.g., base stations) to prevent adverse effects from resource failures. When there are many resources to inspect and they are spread out, it is often necessary to plan inspection routes for the resources in advance.

[0003] In the existing technology, planning is often done manually, that is, judging based on personal experience and planning the shortest path. However, due to differences in personal experience and resources, this method may result in a long time and low efficiency. Summary of the Invention

[0004] The present disclosure provides a patrol route planning method, device, electronic device, and storage medium to at least solve the above-mentioned problems. The technical solutions of the present disclosure are as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a method for planning an inspection path is provided, comprising:

[0006] In response to the path planning operation, obtaining resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation;

[0007] Inputting the resource-related information and the subject-related information into a target path planning model to generate a candidate inspection path for the multiple resources to be inspected based on the resource-related information and the subject-related information;

[0008] Obtaining the cumulative inspection time required to inspect the multiple resources to be inspected using the selected inspection path;

[0009] When the difference between the accumulated inspection time and the remaining inspection time of the inspection subject meets a preset requirement, the to-be-selected inspection path is determined as the target inspection path.

[0010] According to a second aspect of an embodiment of the present disclosure, there is provided an inspection path planning device, comprising:

[0011] An information acquisition module, configured to, in response to a path planning operation, acquire resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation;

[0012] a path generation module, configured to input the resource-related information and the subject-related information into a target path planning model, so as to generate a candidate inspection path for the plurality of resources to be inspected based on the resource-related information and the subject-related information;

[0013] A duration acquisition module, configured to acquire the cumulative inspection duration required for inspecting the plurality of resources to be inspected along the selected inspection path;

[0014] The path determination module is configured to determine the candidate inspection path as the target inspection path when the difference between the accumulated inspection time and the remaining inspection time of the inspection subject meets a preset requirement.

[0015] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0016] processor;

[0017] a memory for storing instructions executable by the processor;

[0018] The processor is configured to execute the instructions to implement the method as described in any one of the first aspects.

[0019] According to a fourth aspect of an embodiment of the present disclosure, a storage medium is provided. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device executes the method as described in any one of the first aspects.

[0020] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, which includes readable program instructions. When the readable program instructions are executed by a processor of an electronic device, the electronic device executes the method as described in any one of the first aspects.

[0021] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects: In the embodiments of the present disclosure, by responding to the path planning operation, the resource-related information of the multiple resources to be inspected and the subject-related information of the inspection subject indicated by the path planning operation are obtained; the resource-related information and the subject-related information are input into the target path planning model to generate a selected inspection path for the multiple resources to be inspected based on the resource-related information and the subject-related information; the cumulative inspection time required for inspecting the multiple resources to be inspected using the selected inspection path is obtained; when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements, the selected inspection path is determined as the target inspection path. In this way, through the target path planning model, an inspection path can be automatically generated for the resources to be inspected based on the relevant information of the resources to be inspected and the inspection subject, thereby eliminating the need for manual path planning and improving the intelligence and efficiency of path planning. At the same time, since the candidate inspection path is determined as the target inspection path only when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements, this can avoid the impact of the cumulative inspection time being too long or too short on the inspection subject and improve the quality of inspection path planning.

[0022] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0024] Figure 1 is a flow chart showing a method for planning an inspection path according to an exemplary embodiment;

[0025] Figure 2 is a schematic diagram showing a process of generating a planned path according to an exemplary embodiment;

[0026] Figure 3 is a schematic diagram of a scenario according to an exemplary embodiment;

[0027] Figure 4 is a flow chart showing another inspection path planning method according to an exemplary embodiment;

[0028] Figure 5 The figure is a block diagram of a patrol route planning device according to an exemplary embodiment. DETAILED DESCRIPTION

[0029] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0030] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure as detailed in the appended claims.

[0031] Figure 1 FIG. 1 is a flow chart showing a method for planning an inspection path according to an exemplary embodiment. Figure 1 As shown, the following steps may be included:

[0032] Step 101: In response to a path planning operation, obtain resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation.

[0033] In an embodiment of the present invention, the aforementioned resources may be equipment requiring inspection within a base station, computer room, or factory building. Accordingly, the aforementioned resources to be inspected may be equipment that has not yet been inspected within an inspection cycle. The aforementioned path planning operation may be automatically triggered upon receiving a list of resources to be inspected, or may be triggered upon receiving a path planning control for a list of resources to be inspected, and this is not limited in the embodiment of the present invention. Accordingly, the multiple resources to be inspected indicated by the aforementioned path planning operation may be the received list of resources to be inspected, or may be selected from all inspectable resources as required.

[0034] The inspection subject mentioned above refers to the subject responsible for completing the inspection of the inspection resources, which can be an inspection personnel or an intelligent device dedicated to inspection, for example, an inspection robot.

[0035] Furthermore, the resource-related information refers to information related to the attributes of the multiple resources to be inspected, and may include information such as the geographical location of each resource to be inspected, the importance of each resource, and the inspection method. Correspondingly, the subject-related information refers to information related to the attributes of the inspection subject, and may include information such as the departure location of the inspection subject and the inspection speed. It is understood that both the resource-related information and the subject-related information have a certain impact on the duration of the inspection.

[0036] Step 102: Input the resource-related information and the subject-related information into a target path planning model to generate a candidate inspection path for the plurality of resources to be inspected based on the resource-related information and the subject-related information.

[0037] The target path planning model may be pre-trained, and may be trained based on the sample resource-related information and sample subject-related information of the training sample. Specifically, the target path planning model may include a path calculation layer, which may calculate the optimal inspection sequence between the resources to be inspected based on the resource-related information and subject-related information. The optimal inspection sequence may be based on the shortest distance between any two resources to be inspected, and / or the shortest distance time, and / or the inspection level from high to low, etc., thereby obtaining the above-mentioned inspection path to be selected.

[0038] Step 103: Obtain the cumulative inspection time required for inspecting the multiple resources to be inspected using the selected inspection path.

[0039] The cumulative inspection duration refers to the time required for the inspection subject to complete the inspection of the multiple resources to be inspected according to the selected inspection path, which may include the time required to inspect each resource to be inspected and the time required for the inspection path.

[0040] Specifically, the total time required for the inspection subject to inspect each resource to be inspected, as well as the traffic time required for the section from each resource to be inspected to the next resource to be inspected in the above-mentioned selected inspection path can be obtained respectively, so that the traffic time and inspection time can be used as the above-mentioned cumulative inspection time.

[0041] Step 104: If the difference between the accumulated inspection duration and the remaining inspection duration of the inspection subject meets a preset requirement, the candidate inspection path is determined as a target inspection path.

[0042] Among them, the remaining inspection time of the above-mentioned inspection subject refers to the remaining time that the inspection subject can use to complete the inspection within this inspection cycle. The above-mentioned inspection cycle can be one day. Accordingly, the above-mentioned remaining inspection time can be determined based on the current time and the standard inspection time of the inspection subject in one day. For example, when the standard inspection time of the inspection subject in this inspection cycle is (8:00~18:00), and the current time is 12:00, the time available to complete the inspection is 6h, that is, the above-mentioned remaining inspection time is 6h.

[0043] Specifically, when the difference between the cumulative inspection time and the remaining inspection time meets the preset requirements, it indicates that the inspection subject can complete the inspection of the above-mentioned resources to be inspected within its own inspection time, and at the same time, the time required to complete the inspection will not exceed the inspection time of the inspection subject too much, thereby avoiding the impact of the inspection subject's time allocation other than inspection due to the excessive time spent on completing the inspection. Accordingly, the above-mentioned preset requirements can be that the cumulative inspection time will not be much greater than the remaining inspection time, nor will it be much less than the remaining inspection time, or that the cumulative inspection time and the remaining inspection time are close enough, and a difference threshold can be set. When the difference between the two is within the difference threshold, it is determined that the preset requirements are met. The above-mentioned difference threshold can be set according to actual needs. For example, it can be set to 20 minutes, of course, it can also be 10 minutes or 5 minutes, etc. The embodiment of the present invention does not limit this.

[0044] In summary, the embodiment of the present disclosure provides a method for patrol path planning, which obtains resource-related information of multiple resources to be patrolled and subject-related information of the patrol subject indicated by the path planning operation in response to the path planning operation; inputs the resource-related information and the subject-related information into a target path planning model to generate a candidate patrol path for the multiple resources to be patrolled based on the resource-related information and the subject-related information; obtains the cumulative patrol time required for patrolling the multiple resources to be patrolled using the candidate patrol path; and determines the candidate patrol path as the target patrol path when the difference between the cumulative patrol time and the remaining patrol time of the patrol subject meets the preset requirements. In this way, through the target path planning model, a patrol path can be automatically generated for the resource to be patrolled based on the relevant information of the resource to be patrolled and the patrol subject, thereby eliminating the need for manual path planning and improving the intelligence and efficiency of path planning. At the same time, since the candidate inspection path is determined as the target inspection path only when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements, this can avoid the impact of the cumulative inspection time being too long or too short on the inspection subject and improve the quality of inspection path planning.

[0045] Optionally, the resource-related information includes the resource location of each of the resources to be inspected, and the subject-related information includes the inspection starting position of the inspection subject. The above operation of generating the selected inspection paths for the multiple resources to be inspected based on the resource-related information and the subject-related information may specifically include the following steps in the embodiment of the present disclosure:

[0046] Step 201: Based on the resource location of each resource to be inspected and the inspection start location, determine a starting resource from the multiple resources to be inspected, and divide the starting inspection resources into planned groups.

[0047] Among them, the above-mentioned resource location refers to the geographical location of the resource, which can be the latitude and longitude information of the resource. The above-mentioned inspection starting position refers to the starting position of the inspection subject when conducting the inspection, or it can be the latitude and longitude information of the inspection subject at the starting point.

[0048] Among them, the above-mentioned starting resource refers to the resource to be inspected first. Specifically, the first resource to be inspected can be selected from the resources to be inspected based on the location of the above-mentioned resource and the inspection starting position. For example, the resource closest to the inspection starting position can be selected as the starting resource.

[0049] The planned group refers to a resource group for which path planning has been completed. It can be in array form. It is understood that the planned group can be initially empty. After the starting resource is determined, the starting resource can be used as the first resource in the planned group. Specifically, the identifier of the resource to be inspected can be used as its value in the planned group. The identifier can be a code for each resource to be inspected, or a unique identifier for each resource to be inspected.

[0050] Step 202: Take the starting resource as the target resource, select resources from the unplanned group whose arrival paths to the target resource meet preset requirements, and assign them to the planned group; the unplanned group includes the resources to be inspected that do not belong to the planned group among the multiple resources to be inspected.

[0051] Among them, the above-mentioned unplanned group refers to a resource group for which path planning has not yet been performed. It can be understood that the initial state of the above-mentioned unplanned group can be to include all resources to be inspected, so that each time a resource is planned, it can be deleted from the unplanned group and added to the planned group.

[0052] The preset requirement can be the shortest travel time to the target resource, or the shortest straight-line distance to the target resource, or the shortest straight-line distance and the shortest travel time. The specific setting can be based on actual needs and is not limited in this embodiment of the present invention. Specifically, the starting resource can be used as the target resource, and the straight-line distance between each other resource to be inspected and the target resource can be obtained in sequence, and the straight line connecting the two can be used as the arrival path between the two. The straight-line distance can be obtained based on the latitude and longitude information of the target resource and the other resources to be inspected.

[0053] Step 203: Update the target resource to the resource that was most recently assigned to the planned group, and re-execute the step of selecting a resource from the unplanned group whose arrival path to the target resource meets the preset requirements, and when the unplanned group is empty, generate the to-be-selected inspection path based on the order in which each of the to-be-inspected resources is assigned to the planned group.

[0054] Among them, the resource that was most recently divided into the planned group refers to the resource that was most recently selected and meets the preset requirements. It can be understood that inspecting resources is to inspect the resources to be inspected in turn, so the inspection path is to complete the inspection of a resource to be inspected, and then inspect the next resource to be inspected. That is to say, the path to be inspected is composed of multiple small paths, each of which is connected to two resources to be inspected. Whether the arrival path of each small path meets the requirements depends on the end resource of the small path. Therefore, in an embodiment of the present invention, after the resources are divided into the planned group, the resource that meets the preset requirements was selected most recently as the target resource, and the selection of resources that meet the preset requirements from the unplanned group is re-executed until there are no unplanned resources. Then, the arrangement order of the resources in the planned group can be used as the path to be inspected, that is, the order in which the resources to be inspected are divided into the planned group is used as the inspection order to be selected, thereby obtaining the path to be inspected.

[0055] Specifically, the embodiment of the present invention can utilize the idea of ​​Dijkstra's algorithm, determine the starting resource through the inspection starting position of the inspection subject, and then expand outward layer by layer with the starting resource as the center, and each time select resources that meet the preset requirements for expansion until it reaches the end point.

[0056] In an embodiment of the present invention, the resource-related information includes the resource location of each of the resources to be inspected, and the subject-related information includes the inspection starting position of the inspection subject; based on the resource location of each of the resources to be inspected and the inspection starting position, the starting resource is determined from the multiple resources to be inspected, and the starting inspection resource is divided into a planned group; the starting resource is used as the target resource, and a resource whose arrival path with the target resource meets the preset requirements is selected from the unplanned group, and is divided into the planned group; the unplanned group includes the resources to be inspected that do not belong to the planned group among the multiple resources to be inspected; the target resource is updated to the resource that was most recently divided into the planned group, and the step of selecting a resource whose arrival path with the target resource meets the preset requirements from the unplanned group is re-executed, and when the unplanned group is empty, the inspection path to be selected is generated based on the order in which each of the resources to be inspected is divided into the planned group. In this way, by setting up planned groups and unplanned groups, resources that meet the preset requirements can be determined in sequence from the unplanned group based on the starting resources, and divided into the planned groups. In this way, the inspection path to be selected can be obtained according to the order in which each resource to be inspected is divided into the planned group, and the arrival path between each resource to be inspected in the inspection path to be selected can meet the preset requirements, thereby improving the quality of the generated inspection path to be selected.

[0057] Optionally, the subject-related information further includes a movement mode of the inspection subject. The operation of selecting a resource from the unplanned group whose arrival path to the target resource meets preset requirements may include the following steps in the embodiment of the present disclosure:

[0058] Step 301: Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource, the path distance and the required arrival time of the arrival path between the target resource and each resource included in the unplanned group are obtained; the road condition coefficient is optimized during the training process of the target path planning model.

[0059] Step 302: Based on the path distances and required arrival times of the arrival paths between the target resource and each resource included in the unplanned group, select a resource whose arrival path to the target resource meets preset requirements.

[0060] Among them, the above-mentioned movement mode refers to the transportation mode of the inspection subject. It can be understood that different movement modes correspond to different movement speeds, so the above-mentioned movement mode can correspond to the movement speed of the inspection subject. Specifically, the movement speeds corresponding to different movement modes can be pre-set. For example, the movement modes can include walking, cycling, engineering vehicles, etc. Accordingly, the movement speed corresponding to the walking mode can be 5 kilometers per hour, the movement speed corresponding to the cycling mode can be 15 kilometers per hour, and the movement speed corresponding to the engineering vehicle mode can be 40 kilometers per hour. Of course, the movement speeds corresponding to the specific different movement modes can be set according to actual conditions. The embodiment of the present invention only shows the average values ​​under several conditions, and the embodiment of the present invention does not limit this.

[0061] Among them, the above-mentioned road condition coefficient can be used to characterize traffic complexity. The higher the road condition coefficient value, the more complex the traffic, and the more time the inspection subject spends on the road. Specifically, due to the different locations of different resources, some resources may exist in standard communities, some resources may exist in commercial buildings, and some resources may exist in urban villages. It can be understood that the traffic complexity in standard communities is relatively low, followed by commercial buildings, while the road condition complexity in urban villages is relatively high. Therefore, the target path planning model in the embodiment of the present invention can determine the corresponding road condition coefficient according to the location of different resources, as a weighted processing index for the resource. The specific road condition coefficient value can be optimized during the training process of the model. For example, the standard community can be 1.1, the commercial building can be 1.2, and the urban village system can be 1.3.

[0062] Specifically, for any unplanned resource, the straight-line distance between the target resource and the unplanned resource can be used as the path distance. Specifically, taking the longitude and latitude coordinates of the target resource as A (MLonA, MLatA) and any unplanned resource as B (MLonB, MLatB) as an example, the straight-line distance between the two can be obtained as:

[0063] S=R*Arccos(sin(MLatA*Pi / 180)*sin(MLatB*Pi / 180)+cos(MLatA*Pi / 180)*cos(MLatB*Pi / 180)*cos((MLonA-MLonB)*Pi / 180))*Pi / 180

[0064] Among them, the above R is the radius of the earth, which is calculated using 6371.004 kilometers.

[0065] Furthermore, the arrival time can be calculated by T=S / V*K, where S is the straight-line distance, V is the moving speed corresponding to the moving mode, and K is the road condition coefficient corresponding to the location of each resource.

[0066] Furthermore, after obtaining the path distance and arrival time of the arrival path between the target resource and other unplanned resources, the resource with a shorter arrival time can be preferentially selected as the next inspection resource. When there are multiple unplanned resources with the same arrival time, the resource with a shorter path distance can be selected as the next inspection resource. Of course, different preset requirements can also be set, and different preset requirements can be set according to different inspection needs.

[0067] In an embodiment of the present invention, the subject-related information also includes the movement mode of the inspection subject; based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource, the path distance of the arrival path between the target resource and each resource included in the unplanned group and the required arrival time are obtained; the road condition coefficient is optimized during the training process of the target path planning model; based on the path distance of the arrival path between the target resource and each resource included in the unplanned group and the required arrival time, a resource whose arrival path to the target resource meets the preset requirements is selected. In this way, multiple factors including the location of the resource, the movement mode, and the road condition coefficient that have a certain impact on the inspection time can be comprehensively considered, and multiple dimensions can be combined to plan the inspection route to improve the effectiveness of the generated inspection route.

[0068] Optionally, the operation of obtaining the path distance and required arrival time of the arrival path between the target resource and each resource included in the unplanned group based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource may specifically include the following steps in an embodiment of the present invention:

[0069] Step 401: When the resource levels of the resources included in the unplanned group are the same and there are no resources in the unplanned group whose inspection method is remote inspection, based on the resource location of each resource to be inspected, the movement method, and the road condition coefficient corresponding to the location of each resource, obtain the path distance and the required arrival time of the arrival path between the target resource and each resource included in the unplanned group.

[0070] The resource level refers to the maintenance type of the resource. The higher the resource level, the higher the priority of the resource, and the resource should be inspected first. Specifically, each resource can be divided into four categories: A urgent, B emergency, C general, and D ordinary, based on the number of people covered by the resource, coverage range, community attributes, and resource attributes. Urgent usually means a major fault occurs and needs to be inspected and resolved immediately.

[0071] Among them, the above-mentioned inspection methods can include remote inspection and on-site inspection. It can be understood that remote inspection means that there is no need to go to the location of the resource for inspection, and the inspection can be completed remotely. Therefore, for resources whose inspection method is remote inspection, the arrival time is 0, and only the detection time is calculated. Correspondingly, on-site inspection means that it is necessary to go to the location of the resource for inspection, so its inspection time = arrival time + detection time. Specifically, the arrival time of resources whose inspection method is remote inspection can be assigned a weight of 0, and the arrival time of resources whose inspection method is on-site inspection can be assigned a weight of 1.

[0072] Furthermore, when the resource levels of the resources in the unplanned group are the same and there is no remote inspection mode, it indicates that there are no resources in the current unplanned resources that need to be individually prioritized. At this time, the path distance and arrival time between the target resource and other unplanned resources can be directly obtained, and further judgment can be made based on the path distance and arrival time.

[0073] In an embodiment of the present invention, by ensuring that the resource levels of the resources included in the unplanned group are the same and that there are no resources in the unplanned group whose inspection mode is remote inspection, the path distance and required arrival time of the arrival path between the target resource and the resources included in the unplanned group are obtained based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource. In this way, when the resource levels of the unplanned resources are the same and there is no resource in the unplanned group whose inspection mode is remote inspection, the path distance and arrival time between the target resource and other unplanned resources can be directly obtained, and further judgment can be made based on the path distance and arrival time, thereby taking both time and distance into consideration for path planning.

[0074] Optionally, the embodiment of the present invention may further include the following steps:

[0075] Step 501: When the resource levels of the resources included in the unplanned group are different, select a resource whose arrival path meets a preset requirement according to the resource level of each resource.

[0076] Among them, when the resource levels of the resources included in the above-mentioned unplanned group are different, it indicates that there are different priority levels in the current unplanned resources. At this time, the resource with the highest resource level can be preferentially selected as the next resource, A first, B second, then C, and finally D, so as to facilitate priority inspection to avoid affecting the normal operation of the resources.

[0077] Step 502: When the resource levels of the resources included in the unplanned group are the same, select the resource whose arrival path meets the preset requirement from the resources in the unplanned group whose inspection mode is remote inspection.

[0078] Correspondingly, when the resource levels of various resources are the same, it indicates that there are no resources in the currently unplanned resources that require priority inspection. At this time, resources whose inspection method is remote inspection can be given priority. It can be understood that remote inspection does not require time to be spent on transportation, so the time required is usually much less than that of resources with other inspection methods. Therefore, resources with remote inspection can be inspected first.

[0079] Furthermore, in the case where there are multiple resources with remote inspection mode, selection can be further made according to the inspection time of each resource, with priority being given to resources with shorter inspection time.

[0080] When the resource levels of the resources included in the unplanned group are the same and there is no resource whose inspection mode is remote inspection, the operation of selecting a resource whose arrival path to the target resource meets preset requirements based on the path distances and required arrival times of the arrival paths between the target resource and the resources included in the unplanned group may specifically include the following steps:

[0081] Step 503: Obtain the inspection time required for each resource based on the path distance and the arrival time, and select a resource whose inspection time required meets a preset requirement.

[0082] The inspection time mentioned above refers to the sum of the arrival time and the detection time. The detection time refers to the time required for the resource to complete the detection itself, which can be obtained based on the historical time of similar resources. Among them, similar resources refer to resources with the same model and the same purpose. The detection time of similar resources is usually closer. Specifically, the average time, maximum time, and minimum time can be obtained from the historical time of similar resources. According to the three-point estimation method, the detection time Te = (To + 4Tm + Tp) / 6 is obtained, where To is the optimistic estimate, that is, the historical minimum time, Tm is the most likely estimate, is the average time, and correspondingly, Tp is the pessimistic estimate, is the maximum time.

[0083] Furthermore, when the levels of the resources are the same and there are no resources requiring remote inspection, the inspection time required for each resource can be calculated, and the resource with the shortest inspection time can be selected as the next planned resource.

[0084] In an embodiment of the present invention, when the resource levels of the resources included in the unplanned group are different, the resources whose arrival paths meet the preset requirements are selected according to the resource levels of the resources; when the resource levels of the resources included in the unplanned group are the same, the resources whose arrival paths meet the preset requirements are selected from the resources in the unplanned group whose inspection mode is remote inspection; when the resource levels of the resources included in the unplanned group are the same and there are no resources whose inspection mode is remote inspection, the inspection time required for each resource is obtained based on the path distance and the arrival time, and the resources whose inspection time meets the preset requirements are selected. In this way, selection can be prioritized according to resource level so that resources with higher levels are inspected first, and then resources with remote inspection can be selected. Finally, selection can be made according to the inspection time required for each resource, so that the inspection requirements and inspection time required for each resource can be comprehensively considered to generate an inspection path that takes into account multiple factors.

[0085] Figure 2 FIG. 1 is a flow chart showing a process of generating a planned path according to an exemplary embodiment. Figure 2 As shown, this may include:

[0086] Step 211: Obtain a list of planned resources.

[0087] Step 212: Read the latest planned resource node.

[0088] Step 213: Determine whether the unplanned resource list is empty. If not, execute step 214. If yes, end the process.

[0089] Step 214: Sort the unplanned resources according to their resource levels.

[0090] Step 215: If there are resources with the same resource level, select the remote resource based on the inspection method. If there are multiple resources, sort them according to the inspection time of each resource, and give priority to the one with the shorter inspection time.

[0091] Among them, the resource time for remote inspection is the detection time.

[0092] Step 216: When there are no remote resources, calculate the distance between the currently planned node and other unplanned resources that are checked on site.

[0093] Step 217: Calculate the travel time between the currently planned node and other unplanned resources.

[0094] Step 218: Select the resource with the minimum detection time + travel time.

[0095] At this time, the resource time for on-site inspection is detection time + travel time.

[0096] Step 219: Divide the selected resources into planned areas and add them to the planned resource list.

[0097] Optionally, the target path planning model is trained based on the following method:

[0098] Step 601: Input the sample resource related information of multiple sample resources and the sample subject related information of the preset inspection subject into the model to be trained, and obtain the inspection path generated by the model to be trained for the multiple sample resources based on the sample resource related information and the sample subject related information as the path to be verified.

[0099] Among them, the above-mentioned sample resources can be randomly selected from all resources, and the above-mentioned preset inspection subject can be any inspection personnel or inspection robot, which can be set according to actual needs. The embodiment of the present invention does not limit this.

[0100] Furthermore, the aforementioned model to be trained may be pre-built and may include an input layer, a computation layer, and an output layer. The input layer may be used to receive resource-related information and subject-related information, and the computation layer may generate an inspection path for the sample resource based on the sample resource-related information and the sample subject-related information in the manner shown in the aforementioned steps, as the path to be verified.

[0101] Step 602: Obtain a first inspection duration consumed when inspecting the sample resource along the path to be verified, and a second inspection duration consumed when inspecting the sample resource not along the path to be verified.

[0102] Step 603: Adjust the model parameters of the to-be-trained model based on the first inspection duration and the second inspection duration until a preset stop condition is reached, and determine the current to-be-trained model as the target path planning model.

[0103] Among them, the above-mentioned first inspection duration is the total duration spent by the above-mentioned preset inspection subject to conduct an inspection of the sample resources according to the path to be verified. Correspondingly, the above-mentioned second inspection duration is the total duration spent by the above-mentioned preset inspection subject not to conduct an inspection of the sample resources according to the above-mentioned path to be verified. Among them, the above-mentioned second inspection duration can be multiple, and can be obtained after the above-mentioned preset inspection subject conducts multiple inspections of the sample resources according to multiple paths different from the above-mentioned path to be verified. Therefore, the model can be positively and negatively verified through the above-mentioned first inspection duration and the second inspection duration.

[0104] The preset stop condition may be that the first inspection duration is less than the second inspection duration. It is understood that, generally, the first inspection duration should be less than the second inspection duration. Therefore, in embodiments of the present invention, when there is a second inspection duration that is less than the first inspection duration, the model parameters may be adjusted until the first inspection duration is less than all second inspection durations. The model parameters may include a road condition coefficient, and may also include other parameters, which are not limited in embodiments of the present invention.

[0105] In an embodiment of the present invention, sample resource related information of multiple sample resources and sample subject related information of a preset inspection subject are input into a to-be-trained model, and an inspection path generated by the to-be-trained model for the multiple sample resources based on the sample resource related information and the sample subject related information is obtained as a to-be-verified path; a first inspection time spent on inspecting the sample resources according to the to-be-verified path and a second inspection time spent on not inspecting the sample resources according to the to-be-verified path are obtained; model parameters of the to-be-trained model are adjusted based on the first inspection time and the second inspection time until a preset stop condition is met, and the current to-be-trained model is determined as the target path planning model. In this way, the to-be-trained model is trained using sample resources and preset inspection subjects, and after obtaining the to-be-verified path, a positive and negative verification is performed on the to-be-verified path to obtain the first inspection time and the second inspection time, respectively. Thus, the model parameters can be adjusted based on the first inspection time and the second inspection time until a target path planning model that meets the requirements is obtained, and then a patrol path that meets the requirements can be generated using the target path planning model, thereby improving generation efficiency and inspection efficiency.

[0106] Optionally, the above-mentioned obtaining of the cumulative inspection duration required for inspecting the plurality of resources to be inspected along the selected inspection path may specifically include the following steps:

[0107] Step 701: Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the resource location, the total path time corresponding to the candidate inspection path is obtained.

[0108] Step 702: Determine the cumulative inspection duration based on the total path time and the inspection duration required for each resource to be inspected.

[0109] The total path duration is the sum of the arrival times between any resource and the next resource in the selected inspection path. Specifically, the total path duration can be calculated by adding the arrival times between any resource and the next resource. Specifically, the arrival time between any resource and the next resource can be calculated using T = S / V * K in the aforementioned step.

[0110] Furthermore, the inspection time required for each resource to be inspected can be based on the historical inspection time of similar resources and obtained through a three-point estimation method, which will not be repeated here. The total path time and the inspection time required for each resource can then be added together to obtain the cumulative inspection time.

[0111] In an embodiment of the present invention, the total path time corresponding to the selected inspection path is obtained based on the resource location of each resource to be inspected, the movement method, and the road condition coefficient corresponding to the location of each resource to be inspected. The cumulative inspection duration is determined based on the total path time and the required inspection duration of each resource to be inspected. In this way, the path time and inspection duration can be comprehensively considered, so that the inspection route can be planned based on time, thereby improving inspection efficiency.

[0112] Optionally, the embodiment of the present invention may further include the following steps:

[0113] Step 801: When the difference between the cumulative inspection duration and the remaining inspection duration of the inspection subject does not meet the preset requirements, delete the end resource in the selected inspection path, or add new resources to be inspected to the multiple resources to be inspected until the difference between the cumulative inspection duration and the remaining inspection duration of the inspection subject meets the preset requirements.

[0114] The above-mentioned end resource refers to the last resource in the inspection path to be selected.

[0115] Specifically, when the difference between the cumulative inspection time and the remaining inspection time does not meet the preset requirements, in one case, the cumulative inspection time may be much greater than the remaining inspection time, indicating that the current cumulative inspection time exceeds the available inspection time of the inspection subject. At this time, the end point resources in the selected inspection path can be deleted until the difference between the two meets the preset requirements.

[0116] In another case, the failure to meet the preset requirements may also be that the cumulative duration is less than the remaining inspection time, indicating that there is still room for inspection for the current inspection subject. At this time, new resources to be inspected can be added, and the path of the current resources to be inspected can be re-planned until the cumulative duration of the planned path is close to or slightly greater than the remaining inspection time of the inspection subject.

[0117] The new resources to be inspected may be obtained by accepting external input, which is not limited in this embodiment of the present invention.

[0118] In an embodiment of the present invention, if the difference between the cumulative inspection duration and the remaining inspection duration of the inspection subject does not meet preset requirements, the terminal resource in the candidate inspection path is deleted, or a new resource to be inspected is added to the plurality of resources to be inspected until the difference between the cumulative inspection duration and the remaining inspection duration of the inspection subject meets the preset requirements. In this way, the candidate inspection path can be corrected based on time until a planned path that meets the requirements is obtained, thereby improving the efficiency of the generated path.

[0119] Figure 3is a schematic diagram of a scenario according to an exemplary embodiment. Figure 3 As shown, the embodiment of the present invention can be applied to a scenario where there are multiple resources to be inspected, and each resource to be inspected is distributed at a different location of the inspection subject.

[0120] Figure 4 FIG. 1 is a flow chart showing another inspection path planning method according to an exemplary embodiment. Figure 4 As shown, the following steps may be included:

[0121] Basic information acquisition, initial route planning, path time estimation, and planned route correction.

[0122] The basic information acquisition may include:

[0123] S1: Obtain the personal information of the operation and maintenance engineer, including working hours and company location.

[0124] Among them, the above-mentioned operation and maintenance engineer refers to the inspection subject, the working hours are the remaining inspection time of the operation and maintenance engineer, and the company location is the starting location of the inspection.

[0125] S2: Obtain the work order information that needs to be processed currently, and use the three-point estimation method to calculate the pre-processing time of each work order based on the historical processing time required for similar work orders.

[0126] Among them, the above-mentioned work orders correspond to inspection resources. Accordingly, the work orders that need to be processed correspond to the resources to be inspected. The preprocessing time of each work order refers to the inspection time of the resources to be inspected, which can be obtained through the three-point estimation method based on the historical time of similar resources.

[0127] Furthermore, the above initial route planning may include:

[0128] S3: First, based on the principle of high work order priority and target location close to the company, preliminarily screen out target preprocessing work orders whose cumulative preprocessing time does not exceed the working time.

[0129] S4: Calculate the weighted processing index of each work order based on the route planning data model.

[0130] S5: Specify a preliminary planning route plan based on the weighted processing index value of the pre-processing work order.

[0131] Among them, the above-mentioned work order priority refers to the resource level of the resources to be inspected. The above-mentioned preliminary screening can be to first screen out the more urgent work orders that will not exceed the working hours of the inspection subject as the target pre-processing work orders when there are many work orders to be processed.

[0132] Among them, the above-mentioned route planning data model refers to the target path planning model, and the weighted processing index refers to the road condition coefficient of the location of each resource.

[0133] Furthermore, the route planning data model can perform preliminary path planning based on the basic information obtained in the above steps and the weighted processing index to obtain a candidate inspection path.

[0134] Furthermore, the above-mentioned path time estimation may include:

[0135] S6: Calculate the total path based on the path plan and estimate the path time based on the moving speed.

[0136] The total path mentioned above refers to the sum of the path distances from any work order to the next work order in the path plan, and the moving speed mentioned above refers to the moving speed of the operation and maintenance engineer, which varies according to the transportation mode of the operation and maintenance engineer.

[0137] Furthermore, the above-mentioned planned route correction may include:

[0138] S7: Based on the total path time and the weighted processing index value of the pre-processing work order, a target pre-processing work order is regenerated when the accumulated time is close to or not greater than the working time.

[0139] S8: Generate a new work order processing route plan based on the corrected pre-processed work order.

[0140] The cumulative duration includes the path time and the detection time. Specifically, the final path time can be obtained based on the path time and the weighted processing index value, and added to the pre-processing time of each work order.

[0141] When the accumulated time is close to or not greater than the working time, it indicates that the difference between the processing time of the current work order and the remaining inspection time of the inspection subject does not meet the preset requirements. At this time, the terminal work order can be deleted or a new work order can be added to obtain a corrected pre-processing work order, and the planned path can be regenerated for the corrected pre-processing work order until the accumulated time is not less than and slightly greater than the working time.

[0142] As can be seen, the embodiment of the present invention understands the business scenarios of resource operation and maintenance inspection, investigates the factors that affect inspection route planning in actual production, establishes an AI big data model and statistical algorithm, comprehensively calculates the resource type, inspection method, inspection duration, and resource location that affect route planning, and then uses the Dijkstra algorithm to calculate the inspection route with the minimum time. Finally, the minimum time planning route is corrected according to the working hours to generate an inspection route planning deployment plan to achieve the purpose of taking into account resource type, path distance, and inspection time, thereby improving inspection efficiency. This further improves the efficiency of network resource inspection and reduces operation and maintenance costs.

[0143] Figure 5 is a block diagram of an inspection path planning device according to an exemplary embodiment. Figure 5 As shown, the device 90 may include:

[0144] An information acquisition module 901 is configured to, in response to a path planning operation, acquire resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation;

[0145] A path generation module 902 is configured to input the resource-related information and the subject-related information into a target path planning model, so as to generate a candidate inspection path for the plurality of resources to be inspected based on the resource-related information and the subject-related information;

[0146] The duration acquisition module 903 is used to obtain the cumulative inspection duration required for inspecting the plurality of resources to be inspected along the selected inspection path;

[0147] The path determination module 904 is configured to determine the candidate inspection path as a target inspection path if the difference between the accumulated inspection duration and the remaining inspection duration of the inspection subject meets a preset requirement.

[0148] Optionally, the resource-related information includes the resource location of each resource to be inspected, and the subject-related information includes the inspection starting location of the inspection subject; the path generation module 902 includes:

[0149] a starting resource determination submodule, configured to determine a starting resource from the plurality of resources to be inspected based on the resource location of each of the resources to be inspected and the inspection starting location, and to divide the starting inspection resources into planned groups;

[0150] a planned group determination submodule, configured to use the starting resource as the target resource, select resources from the unplanned group whose arrival paths to the target resource meet preset requirements, and assign them to the planned group; the unplanned group includes the resources to be inspected that do not belong to the planned group among the multiple resources to be inspected;

[0151] The path generation submodule is used to update the target resource to the resource that was most recently divided into the planned group, and re-execute the step of selecting a resource from the unplanned group whose arrival path to the target resource meets the preset requirements, and when the unplanned group is empty, generate the to-be-selected inspection path based on the order in which each of the to-be-inspected resources is divided into the planned group.

[0152] Optionally, the subject-related information further includes a movement mode of the inspection subject; the planned group determination submodule is specifically configured to:

[0153] Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource, the path distance and the required arrival time of the arrival path between the target resource and each resource included in the unplanned group are obtained; the road condition coefficient is optimized during the training process of the target path planning model;

[0154] Based on the path distance and required arrival time of the arrival path between the target resource and each resource included in the unplanned group, a resource whose arrival path to the target resource meets preset requirements is selected.

[0155] Optionally, the planned group determination submodule is further configured to:

[0156] When the resource levels of the resources included in the unplanned group are the same and there are no resources in the unplanned group whose inspection method is remote inspection, the path distance and the required arrival time of the arrival path between the target resource and the resources included in the unplanned group are obtained based on the resource location of each resource to be inspected, the movement method, and the road condition coefficient corresponding to the location of each resource.

[0157] Optionally, the planned group determination submodule is further configured to:

[0158] In a case where resource levels of the resources included in the unplanned group are different, selecting a resource whose arrival path meets a preset requirement according to the resource level of each resource;

[0159] In a case where the resource levels of the resources included in the unplanned group are the same, selecting a resource whose arrival path meets the preset requirements from the resources in the unplanned group whose inspection mode is remote inspection;

[0160] When the resource levels of the resources included in the unplanned group are the same and there are no resources whose inspection method is remote inspection, the inspection time required for each resource is obtained based on the path distance and the arrival time, and the resources whose inspection time required meets the preset requirements are selected.

[0161] Optionally, the target path planning model is trained based on the following method:

[0162] Inputting sample resource related information of multiple sample resources and sample subject related information of preset inspection subjects into the to-be-trained model, and obtaining inspection paths generated by the to-be-trained model for the multiple sample resources based on the sample resource related information and the sample subject related information as the to-be-verified paths;

[0163] Obtaining a first inspection duration consumed when inspecting the sample resource along the path to be verified, and a second inspection duration consumed when the sample resource is not inspected along the path to be verified;

[0164] The model parameters of the model to be trained are adjusted based on the first inspection duration and the second inspection duration until a preset stop condition is reached, and the current model to be trained is determined as the target path planning model.

[0165] Optionally, the duration acquisition module 903 is specifically configured to:

[0166] Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource to be inspected, the total path time corresponding to the selected inspection path is obtained;

[0167] The cumulative inspection duration is determined based on the total path time and the inspection duration required for each of the resources to be inspected.

[0168] Optionally, the device 90 further includes:

[0169] A resource adjustment module is used to delete the end point resources in the selected inspection path when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject does not meet the preset requirements, or to add new resources to be inspected to the multiple resources to be inspected until the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements.

[0170] In summary, the inspection path planning device provided by the embodiment of the present disclosure obtains resource-related information of multiple resources to be inspected and subject-related information of the inspection subject indicated by the path planning operation in response to the path planning operation; inputs the resource-related information and the subject-related information into the target path planning model to generate a selected inspection path for the multiple resources to be inspected based on the resource-related information and the subject-related information; obtains the cumulative inspection time required for inspecting the multiple resources to be inspected using the selected inspection path; and when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements, determines the selected inspection path as the target inspection path. In this way, through the target path planning model, an inspection path can be automatically generated for the resources to be inspected based on the relevant information of the resources to be inspected and the inspection subject, thereby eliminating the need for manual path planning and improving the intelligence and efficiency of path planning. At the same time, since the candidate inspection path is determined as the target inspection path only when the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements, this can avoid the impact of the cumulative inspection time being too long or too short on the inspection subject and improve the quality of inspection path planning.

[0171] According to one embodiment of the present disclosure, an electronic device is provided, comprising: a processor and a memory for storing processor-executable instructions, wherein the processor is configured to implement the steps in the inspection path planning method in any of the above embodiments when executing.

[0172] According to one embodiment of the present disclosure, a storage medium is further provided. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the steps in the inspection path planning method in any of the above embodiments.

[0173] According to one embodiment of the present disclosure, a computer program product is also provided, which includes readable program instructions. When the readable program instructions are executed by a processor of an electronic device, the electronic device can execute the steps in the inspection path planning method in any of the above embodiments.

[0174] The user information (including but not limited to the user's device information, user personal information, etc.) and related data involved in this disclosure are all information authorized by the user or authorized by all parties.

[0175] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0176] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A patrol route planning method, characterized in that: The method comprises: In response to a path planning operation, obtaining resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation; the resource-related information includes the resource location of each of the resources to be inspected, and the subject-related information includes the inspection starting position of the inspection subject; Inputting the resource-related information and the subject-related information into a target path planning model to determine a starting resource from the multiple resources to be inspected based on the resource location of each resource to be inspected and the inspection starting location, and dividing the starting resources into planned groups; Taking the starting resource as the target resource, selecting resources from the unplanned group whose arrival paths to the target resource meet preset requirements, and assigning them to the planned group; the unplanned group includes the resources to be inspected that do not belong to the planned group among the multiple resources to be inspected; Updating the target resource to the resource most recently assigned to the planned group, and re-performing the step of selecting a resource from the unplanned group whose path to the target resource meets the preset requirements, and generating a candidate inspection path based on the order in which the resources to be inspected are assigned to the planned group if the unplanned group is empty; Obtaining the cumulative inspection time required to inspect the multiple resources to be inspected using the selected inspection path; When the difference between the accumulated inspection time and the remaining inspection time of the inspection subject meets a preset requirement, the to-be-selected inspection path is determined as the target inspection path.

2. The method according to claim 1, characterized in that The subject-related information also includes the movement mode of the inspection subject; the resource selected from the unplanned group whose arrival path to the target resource meets the preset requirements includes: Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource, the path distance and the required arrival time of the arrival path between the target resource and each resource included in the unplanned group are obtained; the road condition coefficient is optimized during the training process of the target path planning model; Based on the path distance and required arrival time of the arrival path between the target resource and each resource included in the unplanned group, a resource whose arrival path to the target resource meets preset requirements is selected.

3. The method according to claim 2, characterized in that The obtaining, based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource, the path distance and the required arrival time of the arrival path between the target resource and each resource included in the unplanned group includes: When the resource levels of the resources included in the unplanned group are the same and there are no resources in the unplanned group whose inspection method is remote inspection, the path distance and the required arrival time of the arrival path between the target resource and the resources included in the unplanned group are obtained based on the resource location of each resource to be inspected, the movement method, and the road condition coefficient corresponding to the location of each resource.

4. The method according to claim 3, characterized in that The method further comprises: In a case where resource levels of the resources included in the unplanned group are different, selecting a resource whose arrival path meets a preset requirement according to the resource level of each resource; In a case where the resource levels of the resources included in the unplanned group are the same, selecting a resource whose arrival path meets the preset requirements from the resources in the unplanned group whose inspection mode is remote inspection; In the case where the resource levels of the resources included in the unplanned group are the same and there is no resource whose inspection mode is remote inspection, the resource whose arrival path to the target resource meets the preset requirements is selected based on the path distance and the required arrival time between the target resource and the resources included in the unplanned group, including The inspection time required for each resource is obtained based on the path distance and the arrival time, and the resource whose inspection time required meets the preset requirement is selected.

5. The method according to claim 2, characterized in that The target path planning model is trained based on the following method: Inputting sample resource related information of multiple sample resources and sample subject related information of preset inspection subjects into the to-be-trained model, and obtaining inspection paths generated by the to-be-trained model for the multiple sample resources based on the sample resource related information and the sample subject related information as the to-be-verified paths; Obtaining a first inspection duration consumed when inspecting the sample resource along the path to be verified, and a second inspection duration consumed when the sample resource is not inspected along the path to be verified; The model parameters of the model to be trained are adjusted based on the first inspection duration and the second inspection duration until a preset stop condition is reached, and the current model to be trained is determined as the target path planning model.

6. The method according to claim 3, characterized in that The obtaining of the cumulative inspection duration required for inspecting the plurality of resources to be inspected along the selected inspection path includes: Based on the resource location of each resource to be inspected, the movement mode, and the road condition coefficient corresponding to the location of each resource to be inspected, the total path time corresponding to the selected inspection path is obtained; The cumulative inspection duration is determined based on the total path time and the inspection duration required for each of the resources to be inspected.

7. The method according to claim 1, characterized in that The method further comprises: If the difference between the cumulative inspection time and the remaining inspection time of the inspection subject does not meet the preset requirements, the end point resource in the selected inspection path is deleted, or new resources to be inspected are added to the multiple resources to be inspected until the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets the preset requirements.

8. A patrol route planning device, characterized in that: The device comprises: An information acquisition module is configured to, in response to a path planning operation, acquire resource-related information of a plurality of resources to be inspected and subject-related information of an inspection subject indicated by the path planning operation; the resource-related information includes the resource location of each of the resources to be inspected, and the subject-related information includes the inspection starting location of the inspection subject; a path generation module, configured to input the resource-related information and the subject-related information into a target path planning model, so as to generate a candidate inspection path for the plurality of resources to be inspected based on the resource-related information and the subject-related information; A duration acquisition module, configured to acquire the cumulative inspection duration required for inspecting the plurality of resources to be inspected along the selected inspection path; A path determination module is configured to determine the candidate inspection path as the target inspection path if the difference between the cumulative inspection time and the remaining inspection time of the inspection subject meets a preset requirement; The path generation module includes: a starting resource determination submodule, configured to determine a starting resource from the plurality of resources to be inspected based on a resource location of each of the resources to be inspected and the inspection starting location, and to divide the starting resources into planned groups; a planned group determination submodule, configured to use the starting resource as the target resource, select resources from the unplanned group whose arrival paths to the target resource meet preset requirements, and assign them to the planned group; the unplanned group includes the resources to be inspected that do not belong to the planned group among the multiple resources to be inspected; The path generation submodule is used to update the target resource to the resource that was most recently divided into the planned group, and re-execute the step of selecting a resource from the unplanned group whose arrival path to the target resource meets the preset requirements, and when the unplanned group is empty, generate the to-be-selected inspection path based on the order in which each of the to-be-inspected resources is divided into the planned group.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device executes the method according to any one of claims 1 to 7.

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