Method, device, system and storage medium for determining unmanned aerial vehicle inspection sequence

Abstract

Embodiments of the present application provide a method, device, system and storage medium for determining a UAV inspection sequence. The method comprises: before a UAV sequentially performs inspection tasks according to task levels, acquiring position information of the inspection tasks of the same task level; generating a plurality of initial inspection areas; determining one or more target inspection areas corresponding to each initial inspection area; determining at least one task execution sequence of the UAV when performing all inspection tasks of each target inspection area; determining a total distance time and a total flight number of times required by the UAV when performing all inspection tasks of each target inspection area according to each task execution sequence; determining an optimal sequence of the UAV when performing all inspection tasks of each target inspection area according to the total distance time and the total flight number of times; and determining an inspection sequence of the UAV when performing the inspection tasks of the same task level according to all optimal sequences, thereby improving the inspection efficiency of the UAV.

Description

Technical Field

[0001] The present application relates to the field of drone inspection technology, and specifically to a method, device, mine inspection system, and storage medium for determining a drone inspection sequence. Background Art

[0002] Drones can be used to inspect large, complex areas, such as mines. For example, drones can perform a wide range of routine inspection tasks at mines, such as routine slope inspections. Drones can regularly take photos of the slopes for evidence collection, then use technical means to identify whether cracks in the slopes have widened, thereby determining whether the slopes are within a safe range. Another example is pre-blast inspections. Before blasting, drones can be used to patrol the area around the ore pile, using AI recognition technology to identify the presence of people and vehicles in images or videos to ensure safety during blasting.

[0003] Currently, the order of drone inspection missions can be managed based on the mission start time. However, the distance between the drone inspection location and the airport (where the drone recharges), as well as the distance between the current drone inspection mission and the next, can be quite large. Therefore, the drone's flight time traveling to the mission location accounts for a significant portion of the flight time. If drones have a large number of daily inspection missions and the inspection locations are relatively scattered, continuing to manage the execution of these missions based on their start time may increase the distance the drone travels to the mission location and the number of round-trip flights to the airport.

[0004] Therefore, the existing solutions for drone inspections require a large number of flights and a lot of time to complete the drone's long-day inspection mission requirements. The drone inspection sequence is not set reasonably, which reduces the efficiency of drone inspections. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a method, device, mine inspection system and storage medium for determining the inspection order of drones, so as to solve the problem of unreasonable inspection order of drones in the prior art.

[0006] To achieve the above objectives, the present application provides, in a first aspect, a method for determining a drone inspection sequence, comprising:

[0007] Before the UAV performs the inspection tasks in sequence according to the task level, it obtains the location information of the inspection tasks of the same task level;

[0008] Generate multiple initial inspection areas based on the location information of inspection tasks of the same task level, the maximum working radius of the drone, and the preset rotation angle;

[0009] Determine one or more target inspection areas corresponding to each initial inspection area according to the number of inspection tasks in each initial inspection area;

[0010] Determine at least one task execution order when the UAV performs all inspection tasks in each target inspection area;

[0011] Determine the total distance traveled and the total number of flights required for the drone to inspect all inspection tasks in each target inspection area according to the execution order of each task;

[0012] Determine the optimal order for drones to perform all inspection tasks in each target inspection area based on the total journey time and total flight sorties;

[0013] The inspection order of drones performing inspection tasks of the same mission level is determined based on the optimal order of all.

[0014] In an embodiment of the present application, determining one or more target inspection areas corresponding to each initial inspection area based on the task number of inspection tasks in each initial inspection area includes: when the task number of inspection tasks in each initial inspection area is greater than a first preset number, dividing each initial inspection area into a first area and a second area of ​​equal area; determining the task number of inspection tasks in the first area and the second area until each initial inspection area is divided into pending inspection areas with a task number less than or equal to the first preset number; judging whether the task number of inspection tasks in each pending inspection area is less than or equal to a second preset number, and the second preset number is less than the first preset number; when the task number of inspection tasks in each pending inspection area is less than or equal to the second preset number, determining the total number of inspection tasks in each pending inspection area and the pending inspection areas adjacent to each pending inspection area; when the total number is less than or equal to a third preset number, merging each pending inspection area with the adjacent pending inspection areas until the total number is greater than the third preset number, to obtain one or more target inspection areas corresponding to each initial inspection area, wherein the third preset number is greater than the second preset number and less than the first preset number.

[0015] In an embodiment of the present application, determining the total distance time and total flight sorties required for the drone to inspect all inspection tasks in each target inspection area in accordance with each task execution sequence includes: for each task execution sequence, when the drone is in the execution position of any inspection task in the task execution sequence, obtaining the remaining working time of the drone; determining the distance time required to fly from the execution position of any inspection task to the execution position of the next inspection task; when the remaining working time is less than the distance time, determining that the drone needs to fly to the installation position of the drone, and the number of flights when the drone inspects in accordance with the task execution sequence is increased by one, and the distance time when the drone inspects in accordance with the task execution sequence is accumulated; when the remaining working time is greater than or equal to the distance time, determining that the drone needs to fly to the execution position of the next inspection task, and the number of flights when the drone inspects in accordance with the task execution sequence is increased by one, and the distance time when the drone inspects in accordance with the task execution sequence is accumulated.

[0016] In an embodiment of the present application, determining the optimal order for drones to perform all inspection tasks in each target inspection area based on the total journey time and the total number of flights includes: when there are multiple minimum total journey times and no multiple minimum total flight sorties, determining the task execution order corresponding to the minimum total flight sorties as the optimal order for the corresponding target inspection area; when there are multiple minimum total journey times and multiple minimum total flight sorties, selecting any one task execution order from the multiple task execution orders corresponding to the minimum total journey time and the minimum total flight sorties as the optimal order for the corresponding target inspection area.

[0017] In an embodiment of the present application, the method also includes: in the process of executing inspection tasks of different task levels in sequence according to the inspection order, determining whether there is an emergency inspection task whose task start time is the current time; if there is an emergency inspection task, controlling the drone to suspend the execution of the current inspection task, and controlling the drone to execute the emergency inspection task.

[0018] In an embodiment of the present application, the method also includes: before the drone performs the inspection task in sequence according to the task level, determining whether there is a time-sensitive task with a fixed task start time; after there is a time-sensitive task and the drone performs inspection in accordance with the inspection order, controlling the drone to suspend the execution of the current inspection task at the fixed task start time, and executing the time-sensitive task according to the fixed task start time.

[0019] In an embodiment of the present application, determining the inspection order when a drone performs an inspection task of the same mission level according to the optimal order of all includes: selecting any target inspection area closest to the drone's airport from all target inspection areas; taking the drone's airport as the center of the circle, determining the arrangement order of all target inspection areas in sequence according to a preset direction; and determining the inspection order according to the optimal order of each target inspection area in the arrangement order.

[0020] A second aspect of the present application provides a device for determining a drone inspection sequence, comprising:

[0021] a memory configured to store instructions;

[0022] The processor is configured to call instructions from the memory and implement the above-mentioned method for determining the inspection order of the drone when executing the instructions.

[0023] A third aspect of the present application provides a mine inspection system, comprising:

[0024] Drones are used to perform inspection tasks within the mining area, including mine slope inspections, production inspections, pre-blasting inspections, and dam body inspections.

[0025] A charging device for supplying power to the drone;

[0026] The above-mentioned device for determining the inspection order of drones.

[0027] A fourth aspect of the present application provides a machine-readable storage medium having instructions stored thereon, which, when executed by a processor, configures the processor to execute the above-mentioned method for determining the inspection order of drones.

[0028] Through the above technical solution, before the UAV performs the inspection tasks in sequence according to the task level, the location information of the inspection tasks of the same task level is obtained; multiple initial inspection areas are generated according to the location information of the inspection tasks of the same task level, the maximum working radius of the UAV and the preset rotation angle; one or more target inspection areas corresponding to each initial inspection area are determined according to the number of inspection tasks in each initial inspection area; at least one task execution order of the UAV when performing all inspection tasks in each target inspection area is determined; the total distance time and total flight sorties required for the UAV to inspect all inspection tasks in each target inspection area according to each task execution order are determined; the optimal order of the UAV when performing all inspection tasks in each target inspection area is determined according to the total distance time and the total flight sorties; the inspection order of the UAV when performing inspection tasks of the same task level is determined according to all the optimal orders, thereby reducing the number of flights and return flights of the UAV and the proportion of non-task time of the UAV, making the inspection order of the UAV more reasonable and improving the inspection efficiency of the UAV.

[0029] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present application but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0031] Figure 1 The following schematically illustrates a flow chart of a method for determining a drone inspection sequence according to an embodiment of the present application;

[0032] Figure 2 A schematic diagram schematically illustrates the distribution of airport locations and mission locations according to an embodiment of the present application;

[0033] Figure 3 A schematic diagram of a target inspection area according to an embodiment of the present application is schematically shown;

[0034] Figure 4 The internal structure diagram of a computer device according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0036] It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of this application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0037] Figure 1 The following schematically shows a flow chart of a method for determining a drone inspection sequence according to an embodiment of the present application. Figure 1 As shown, in one embodiment of the present application, a method for determining a drone inspection sequence is provided, comprising the following steps:

[0038] Step 101: Before the UAV performs inspection tasks in sequence according to the task level, the location information of the inspection tasks of the same task level is obtained.

[0039] Each airport is equipped with a drone to perform inspection missions. The drone's maximum operating time is the maximum duration of a single flight. Upon reaching this maximum operating time, a safety battery alarm is triggered and the drone returns to the airport for recharging. If the drone returns to the airport for recharging before completing its mission, it can resume the unfinished mission after recharging. Otherwise, the drone will proceed to the next inspection mission. In this embodiment, the drone flies in a straight line at a constant speed and at a safe altitude.

[0040] A drone can perform multiple inspection tasks. Each inspection task corresponds to an inspection task model. Each inspection task model defines the task's end location, task level, and task duration. The task end location may include the task's longitude and latitude. The task level can be customized based on actual circumstances. Task duration refers to the estimated time it will take the drone to perform the inspection task. Table 1 below illustrates an inspection task model for one inspection task.

[0041] Table 1

[0042] property name illustrate Lng Mission longitude Mission end location-longitude Lat Mission Latitude Mission end location-latitude Level Task Level cost Task duration Estimated time to complete a single inspection task, in seconds

[0043] When a drone needs to inspect multiple inspection tasks, it can execute all inspection tasks corresponding to the task level in sequence according to the inspection task level. For example, if the inspection task level ranges from 1 to 9, where the lower the value, the higher the task level of the corresponding inspection task, the drone can execute all inspection tasks of different task levels in sequence from 1 to 9.

[0044] Before the drone executes inspection tasks sequentially according to their mission levels, the processor may obtain location information for inspection tasks of the same mission level. Specifically, the processor may traverse multiple inspection task models to obtain inspection task models of the same mission level, and then obtain the location information for the inspection tasks of the same mission level from these models. The location information may include the longitude and latitude of the inspection tasks of the same mission level.

[0045] Step 102: Generate multiple initial inspection areas based on the location information of the inspection tasks of the same task level, the maximum working radius of the drone, and the preset rotation angle.

[0046] The processor can generate multiple initial inspection areas based on the location information of inspection tasks of the same task level, the maximum working radius of the drone, and the preset rotation angle. Among them, the maximum working radius of the drone refers to the farthest distance the drone can fly from the airport where it is located. The preset rotation angle can be customized according to actual conditions. For example, a map coordinate system can be established with the airport where the drone is located as the center of the circle, the north as the y-axis, and the east as the x-axis. Within the circle of the drone's maximum working radius, the entire circular surface can be divided into multiple sector areas according to the preset rotation angle. Afterwards, the maximum working radius can be divided into preset equal parts and a circle can be drawn. At this time, each sector area is divided into a sub-sector area and at least one curved surface area, that is, multiple initial inspection areas are obtained.

[0047] Step 103: Determine one or more target inspection areas corresponding to each initial inspection area according to the number of inspection tasks in each initial inspection area.

[0048] For each initial inspection area, if the number of inspection tasks in the initial inspection area is large, the number of task execution orders in the corresponding area subsequently determined will be very large, resulting in a large amount of computational effort and a long time required to determine the inspection order of the drone. To this end, the processor can determine one or more target inspection areas corresponding to each initial inspection area based on the number of inspection tasks in each initial inspection area. In other words, each initial inspection area can be further divided according to the number of inspection tasks in each initial inspection area to obtain one or more corresponding target inspection areas.

[0049] In an embodiment of the present application, determining one or more target inspection areas corresponding to each initial inspection area based on the task number of inspection tasks in each initial inspection area includes: when the task number of inspection tasks in each initial inspection area is greater than a first preset number, dividing each initial inspection area into a first area and a second area of ​​equal area; determining the task number of inspection tasks in the first area and the second area until each initial inspection area is divided into pending inspection areas with a task number less than or equal to the first preset number; judging whether the task number of inspection tasks in each pending inspection area is less than or equal to a second preset number, and the second preset number is less than the first preset number; when the task number of inspection tasks in each pending inspection area is less than or equal to the second preset number, determining the total number of inspection tasks in each pending inspection area and the pending inspection areas adjacent to each pending inspection area; when the total number is less than or equal to a third preset number, merging each pending inspection area with the adjacent pending inspection areas until the total number is greater than the third preset number, to obtain one or more target inspection areas corresponding to each initial inspection area, wherein the third preset number is greater than the second preset number and less than the first preset number.

[0050] If the number of inspection tasks in each initial inspection area is greater than a first preset number, the processor may divide each initial inspection area into a first area and a second area of ​​equal area. The first preset number may be set based on actual conditions. For example, if the number of tasks in an area exceeds 7, the number of execution orders for all inspection tasks in the area will be too large. Therefore, in order to reduce the amount of subsequent calculations, the number of tasks in an area may be controlled within 7. In this case, the first preset number may be set to 7.

[0051] The processor may determine the number of inspection tasks in the first area and the second area. If the number of inspection tasks in the first area or the second area is greater than a first preset number, the first area or the second area may be divided according to the radius portion corresponding to the first area or the second area. If the first area or the second area is a sub-sector area, the division may obtain another sub-sector area and at least one curved surface area. If the first area or the second area is a curved surface area, the division may obtain at least two curved surface areas, until each initial inspection area is divided into pending inspection areas with a number of tasks less than or equal to the first preset number.

[0052] The distribution of inspection tasks in each pending inspection area is uneven. For example, some pending inspection areas may have no inspection tasks or very few inspection tasks. In this case, the processor may determine whether the number of inspection tasks in each pending inspection area is less than or equal to a second preset number. The second preset number is less than the first preset number. The second preset number can be set based on actual conditions and can be set to 0. If the second preset number is set to 0 and the number of inspection tasks in the pending inspection area is less than or equal to 0, then there may be no inspection tasks in the pending inspection area.

[0053] If the number of inspection tasks in each pending inspection area is less than or equal to a second preset number, the processor may determine the total number of inspection tasks in each pending inspection area and adjacent pending inspection areas. If the total number is less than or equal to a third preset number, the processor may merge each pending inspection area with adjacent pending inspection areas to reduce the number of target inspection areas ultimately obtained. The third preset number is greater than the second preset number and less than the first preset number.

[0054] If the number of inspection tasks in the area after each pending inspection area is merged with the adjacent pending inspection area is less than or equal to the third preset number, the pending inspection areas indirectly adjacent to each pending inspection area can continue to be merged until the total number of inspection tasks in the merged area is greater than the third preset number, and one or more target inspection areas corresponding to each initial inspection area are obtained.

[0055] Step 104: Determine at least one task execution order when the UAV performs all inspection tasks in each target inspection area.

[0056] The processor can determine at least one task execution order for the drone when performing all inspection tasks in each target inspection area. Specifically, the at least one task execution order can be determined using a permutation algorithm or an enumeration algorithm. For example, if the number of inspection tasks in a target inspection area is n, then there are n! task execution orders for the inspection tasks in that target inspection area.

[0057] Step 105: Determine the total distance time and total flight times required for the UAV to inspect all inspection tasks in each target inspection area according to the execution order of each task.

[0058] The processor can determine the total distance time and total flight sorties required for the drone to inspect all inspection tasks of each target inspection area according to each task execution sequence. In an embodiment of the present application, determining the total distance time and total flight sorties required for the drone to inspect all inspection tasks of each target inspection area according to each task execution sequence includes: for each task execution sequence, when the drone is at the execution position of any inspection task under the task execution sequence, obtaining the remaining working time of the drone; determining the distance time required to fly from the execution position of any inspection task to the execution position of the next inspection task; when the remaining working time is less than the distance time, determining that the drone needs to fly to the installation position of the drone, and the number of flight sorties when the drone inspects according to the task execution sequence is increased by one, and the distance time when the drone inspects according to the task execution sequence is accumulated; when the remaining working time is greater than or equal to the distance time, determining that the drone needs to fly to the execution position of the next inspection task, and the number of flight sorties when the drone inspects according to the task execution sequence is increased by one, and the distance time when the drone inspects according to the task execution sequence is accumulated.

[0059] For each task execution sequence, when the drone is at the execution location of any inspection task in the task execution sequence, the remaining operating time of the drone is obtained. The remaining operating time of the drone can be determined based on the remaining battery charge of the drone. The processor can determine the required travel time from the execution location of any inspection task to the execution location of the next inspection task. Specifically, the required travel time can be determined based on the flight speed of the drone and the distance between the execution location of any inspection task and the execution location of the next inspection task.

[0060] like Figure 2 As shown in the figure, a schematic diagram of the distribution of airport locations and task locations is provided. The figure shows airport a0, and tasks 1, 2, and 3. The time required to execute task 1 is t1, the time required to execute task 2 is t2, and the time required to execute task 3 is t3. The distance between task 1 and task 2 is l 12 , the distance between mission 1 and airport a0 is l 01 , the distance between task 1 and task 3 is l 13 , the distance between task 2 and task 3 is l 23 , the distance between mission 2 and airport a0 is l 20 , the distance between mission 3 and airport a0 is l 30. Among them, the distance between any two locations can be determined by the longitude and latitude of any two locations. When the remaining working time is less than the distance time, the processor can determine that the drone needs to fly to the installation location of the drone, that is, the airport of the drone. At this time, the number of flights of the drone when inspecting in the order of task execution increases by one, and the distance time taken by the drone when inspecting in the order of task execution is accumulated. When the remaining working time is greater than or equal to the distance time, the processor can determine that the drone needs to fly to the execution location of the next inspection task, and the number of flights of the drone when inspecting in the order of task execution increases by one, and the distance time taken by the drone when inspecting in the order of task execution is accumulated.

[0061] When the UAV does not need to fly to the execution location of the next inspection task, that is, when the UAV reaches the execution location of the last inspection task in the task execution sequence, the total distance time required for the UAV to inspect all inspection tasks in each target inspection area according to each task execution sequence can be obtained based on the time it takes to fly from the execution location of the last inspection task to the airport and the current accumulated time. The total number of flights required for the UAV to inspect all inspection tasks in each target inspection area according to each task execution sequence can be obtained by adding one to the currently accumulated number of flights.

[0062] Step 106: Determine the optimal order for the drones to perform all inspection tasks in each target inspection area based on the total distance time and the total number of flights.

[0063] The processor can determine the optimal order for the drone to perform all inspection tasks for each target inspection area based on the total journey time and the total number of flights. In an embodiment of the present application, determining the optimal order for the drone to perform all inspection tasks for each target inspection area based on the total journey time and the total number of flights includes: when there are multiple minimum total journey times and no multiple minimum total number of flights, determining the task execution order corresponding to the minimum total number of flights as the optimal order for the corresponding target inspection area; when there are multiple minimum total journey times and multiple minimum total number of flights, selecting any one task execution order from the multiple task execution orders corresponding to the minimum total journey time and the minimum total number of flights as the optimal order for the corresponding target inspection area.

[0064] If there are multiple minimum total journey times but no multiple minimum total flight sorties, the processor may determine the task execution order corresponding to the minimum total flight sorties as the optimal order for the corresponding target inspection area. If there are multiple minimum total journey times and multiple minimum total flight sorties, the processor may select one task execution order from the multiple task execution orders corresponding to the minimum total journey time and the minimum total flight sorties as the optimal order for the corresponding target inspection area.

[0065] Step 107: Determine the inspection order of the drones when performing inspection tasks of the same task level based on all the optimal orders.

[0066] The processor can determine the inspection order of the drone when performing inspection tasks of the same mission level based on the overall optimal order. In an embodiment of the present application, determining the inspection order of the drone when performing inspection tasks of the same mission level based on the overall optimal order includes: selecting any target inspection area closest to the drone's airport from all target inspection areas; determining the arrangement order of all target inspection areas in a predetermined direction with the drone's airport as the center; and determining the inspection order based on the optimal order of each target inspection area in the arrangement order.

[0067] The processor can select any target inspection area closest to the drone's airport from all target inspection areas. The processor can use the drone's airport as the center of the circle and determine the arrangement order of all target inspection areas in a preset direction. The preset direction can be a direction away from the center of the circle in a clockwise or counterclockwise direction. For example, Figure 3 Figure 1 shows a schematic diagram of target inspection areas. The target inspection areas include R11 to R28. The order of arrangement can be R11, R12…R17, R18, R21, R22…R27, R28, or R18, R17…R12, R11, R28, R27…R22, R21. The processor can determine the inspection order based on the optimal order for each target inspection area in the arrangement.

[0068] In an embodiment of the present application, the method also includes: in the process of executing inspection tasks of different task levels in sequence according to the inspection order, determining whether there is an emergency inspection task whose task start time is the current time; if there is an emergency inspection task, controlling the drone to suspend the execution of the current inspection task, and controlling the drone to execute the emergency inspection task.

[0069] Drones can also perform emergency inspection missions. These emergency inspection missions can also correspond to inspection mission models. Specifically, the mission level in the inspection mission model for emergency inspection missions can be set to level 0. While executing inspection missions of different mission levels in sequence, the processor can determine whether there is an emergency inspection mission with a task start time equal to the current time, i.e., an inspection mission that needs to be executed immediately. If an emergency inspection mission exists, the processor can control the drone to pause the current inspection mission and control the drone to execute the emergency inspection mission.

[0070] In an embodiment of the present application, the method also includes: before the drone performs the inspection task in sequence according to the task level, determining whether there is a time-sensitive task with a fixed task start time; after there is a time-sensitive task and the drone performs inspection in accordance with the inspection order, controlling the drone to suspend the execution of the current inspection task at the fixed task start time, and executing the time-sensitive task according to the fixed task start time.

[0071] Drones can also perform time-sensitive tasks. These tasks can also correspond to inspection task models. Specifically, the inspection task model for time-sensitive tasks can also include a task start execution time. Before the drone executes inspection tasks sequentially according to task level, the processor can determine whether there are time-sensitive tasks with fixed task start times. If a time-sensitive task exists and the drone performs inspections according to the inspection sequence, the processor can control the drone to pause the current inspection task at the fixed task start time and then execute the time-sensitive task at the fixed task start time.

[0072] Through the above technical solution, before the UAV performs the inspection tasks in sequence according to the task level, the location information of the inspection tasks of the same task level is obtained; multiple initial inspection areas are generated according to the location information of the inspection tasks of the same task level, the maximum working radius of the UAV and the preset rotation angle; one or more target inspection areas corresponding to each initial inspection area are determined according to the number of inspection tasks in each initial inspection area; at least one task execution order of the UAV when performing all inspection tasks in each target inspection area is determined; the total distance time and total flight sorties required for the UAV to inspect all inspection tasks in each target inspection area according to each task execution order are determined; the optimal order of the UAV when performing all inspection tasks in each target inspection area is determined according to the total distance time and the total flight sorties; the inspection order of the UAV when performing inspection tasks of the same task level is determined according to all the optimal orders, thereby reducing the number of flights and return flights of the UAV and the proportion of non-task time of the UAV, making the inspection order of the UAV more reasonable and improving the inspection efficiency of the UAV.

[0073] Figure 1 FIG. 1 is a flow chart of a method for determining the inspection sequence of a drone in one embodiment. It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily performed at the same time, but can be performed at different times. The order of execution of these sub-steps or stages is not necessarily one by one, but can be performed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0074] In one embodiment, a device for determining a drone inspection sequence is provided, comprising:

[0075] a memory configured to store instructions;

[0076] The processor is configured to call instructions from the memory and implement the above-mentioned method for determining the inspection order of the drone when executing the instructions.

[0077] In one embodiment, a storage medium is provided, on which a program is stored, and when the program is executed by a processor, the method for determining the inspection order of a drone is implemented.

[0078] In one embodiment, a processor is provided, which is used to run a program, wherein the program executes the above-mentioned method for determining the inspection order of drones when running.

[0079] In an embodiment of the present application, a mine inspection system is provided, comprising:

[0080] Drones are used to perform inspection tasks within the mining area, including mine slope inspections, production inspections, pre-blasting inspections, and dam body inspections.

[0081] A charging device for supplying power to the drone;

[0082] The above-mentioned device for determining the inspection order of drones.

[0083] Among them, the charging device can be installed in the airport of the drone.

[0084] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected via a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The database of the computer device is used to store data such as the inspection sequence of the drone. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, a method for determining the inspection sequence of the drone is implemented.

[0085] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0086] An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: before a drone performs inspection tasks in sequence according to the task level, location information of inspection tasks of the same task level is obtained; multiple initial inspection areas are generated based on the location information of inspection tasks of the same task level, the maximum working radius of the drone, and a preset rotation angle; one or more target inspection areas corresponding to each initial inspection area are determined based on the number of inspection tasks in each initial inspection area; at least one task execution order is determined when the drone performs all inspection tasks in each target inspection area; the total distance time and total number of flights required for the drone to inspect all inspection tasks in each target inspection area according to each task execution order; the optimal order for the drone to perform all inspection tasks in each target inspection area based on the total distance time and the total number of flights is determined; and the inspection order when the drone performs inspection tasks of the same task level is determined based on all the optimal orders.

[0087] In one embodiment, determining one or more target inspection areas corresponding to each initial inspection area based on the number of inspection tasks in each initial inspection area includes: dividing each initial inspection area into a first area and a second area of ​​equal area when the number of inspection tasks in each initial inspection area is greater than a first preset number; determining the number of inspection tasks in the first area and the second area until each initial inspection area is divided into pending inspection areas with a number of tasks less than or equal to the first preset number; judging whether the number of inspection tasks in each pending inspection area is less than or equal to a second preset number, the second preset number being less than the first preset number; determining the total number of inspection tasks in each pending inspection area and the pending inspection areas adjacent to each pending inspection area when the number of inspection tasks in each pending inspection area is less than or equal to the second preset number; and merging each pending inspection area with the adjacent pending inspection areas when the total number is less than or equal to a third preset number until the total number is greater than the third preset number, thereby obtaining one or more target inspection areas corresponding to each initial inspection area, wherein the third preset number is greater than the second preset number and less than the first preset number.

[0088] In one embodiment, determining the total distance time and total flight sorties required for a drone to inspect all inspection tasks in each target inspection area in accordance with each task execution sequence includes: for each task execution sequence, when the drone is in the execution position of any inspection task in the task execution sequence, obtaining the remaining working time of the drone; determining the distance time required to fly from the execution position of any inspection task to the execution position of the next inspection task; when the remaining working time is less than the distance time, determining that the drone needs to fly to the installation position of the drone, and the number of flights when the drone inspects in accordance with the task execution sequence is increased by one, and the distance time when the drone inspects in accordance with the task execution sequence is accumulated; when the remaining working time is greater than or equal to the distance time, determining that the drone needs to fly to the execution position of the next inspection task, and the number of flights when the drone inspects in accordance with the task execution sequence is increased by one, and the distance time when the drone inspects in accordance with the task execution sequence is accumulated.

[0089] In one embodiment, determining the optimal order for drones to perform all inspection tasks in each target inspection area based on the total journey time and the total number of flights includes: when there are multiple minimum total journey times and no multiple minimum total flight sorties, determining the task execution order corresponding to the minimum total flight sorties as the optimal order for the corresponding target inspection area; when there are multiple minimum total journey times and multiple minimum total flight sorties, selecting any one task execution order from the multiple task execution orders corresponding to the minimum total journey time and the minimum total flight sorties as the optimal order for the corresponding target inspection area.

[0090] In one embodiment, the method also includes: in the process of executing inspection tasks of different task levels in sequence according to the inspection order, determining whether there is an emergency inspection task whose task start time is the current time; if there is an emergency inspection task, controlling the drone to suspend the execution of the current inspection task, and controlling the drone to execute the emergency inspection task.

[0091] In one embodiment, the method also includes: before the drone performs the inspection task in sequence according to the task level, determining whether there is a time-sensitive task with a fixed task start time; after there is a time-sensitive task and the drone performs inspection in accordance with the inspection order, controlling the drone to suspend the execution of the current inspection task at the fixed task start time, and executing the time-sensitive task according to the fixed task start time.

[0092] In one embodiment, determining the inspection order of a drone when performing inspection tasks of the same mission level based on all optimal orders includes: selecting any target inspection area closest to the drone's airport from all target inspection areas; determining the arrangement order of all target inspection areas in sequence according to a preset direction with the drone's airport as the center of the circle; and determining the inspection order based on the optimal order of each target inspection area in the arrangement order.

[0093] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the method steps for determining the inspection order of a drone.

[0094] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0095] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0096] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0098] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0099] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0100] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0101] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0102] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for determining the inspection sequence of drones, characterized in that: The method comprises: Before the UAV performs the inspection tasks in sequence according to the task level, it obtains the location information of the inspection tasks of the same task level; Generate multiple initial inspection areas according to the location information of the inspection tasks of the same task level, the maximum working radius of the drone, and a preset rotation angle; Determine one or more target inspection areas corresponding to each initial inspection area according to the number of inspection tasks in each initial inspection area; Determining at least one task execution order when the drone performs all inspection tasks in each target inspection area; Determine the total distance time and total number of flights required for the UAV to inspect all inspection tasks in each target inspection area according to the execution order of each task; Determining the optimal order for the drones to perform all inspection tasks in each target inspection area based on the total journey time and the total number of flights; Determining the inspection order of the UAVs when performing inspection tasks of the same mission level according to all the optimal orders; The step of determining one or more target inspection areas corresponding to each initial inspection area according to the number of inspection tasks in each initial inspection area includes: When the number of inspection tasks in each initial inspection area is greater than a first preset number, dividing each initial inspection area into a first area and a second area of ​​equal area; Determining the number of inspection tasks in the first area and the second area until each initial inspection area is divided into pending inspection areas with a number of tasks less than or equal to the first preset number; Determining whether the number of inspection tasks in each pending inspection area is less than or equal to a second preset number, where the second preset number is less than the first preset number; When the number of inspection tasks in each pending inspection area is less than or equal to the second preset number, determining the total number of inspection tasks in each pending inspection area and the pending inspection areas adjacent to each pending inspection area; When the total number is less than or equal to the third preset number, each pending inspection area is merged with the adjacent pending inspection area until the total number is greater than the third preset number, so as to obtain one or more target inspection areas corresponding to each initial inspection area, wherein the third preset number is greater than the second preset number and less than the first preset number.

2. The method for determining the inspection order of drones according to claim 1, characterized in that: The determination of the total distance time and total flight times required for the drone to inspect all inspection tasks of each target inspection area according to the execution order of each task includes: For each task execution sequence, when the drone is in an execution position of any inspection task in the task execution sequence, obtaining the remaining working time of the drone; Determine the time required to fly from the execution location of any inspection task to the execution location of the next inspection task; If the remaining working time is less than the distance time, it is determined that the UAV needs to fly to the installation location of the UAV, and the number of flights of the UAV when inspecting according to the task execution sequence is increased by one, and the distance time when the UAV inspects according to the task execution sequence is accumulated; When the remaining working time is greater than or equal to the distance time, it is determined that the UAV needs to fly to the execution location of the next inspection task, and the number of flights of the UAV when inspecting according to the task execution order is increased by one, and the distance time when the UAV inspects according to the task execution order is accumulated.

3. The method for determining the inspection order of drones according to claim 1, characterized in that: The determining of the optimal order for the UAVs to perform all inspection tasks in each target inspection area according to the total distance time and the total number of flights includes: In the case where there are multiple minimum total journey times and no multiple minimum total flight sorties, the task execution order corresponding to the minimum total flight sorties is determined as the optimal order for the corresponding target inspection area; When there are multiple minimum total journey times and multiple minimum total flight sorties, any one task execution sequence is selected from multiple task execution sequences corresponding to the minimum total journey time and the minimum total flight sortie as the optimal sequence for the corresponding target inspection area.

4. The method for determining the inspection sequence of a drone according to any one of claims 1 to 3, characterized in that: The method further comprises: In the process of executing inspection tasks of different task levels in sequence according to the inspection order, it is determined whether there is an emergency inspection task whose task start time is the current time; In the case where the emergency inspection task exists, the drone is controlled to suspend the execution of the current inspection task, and the drone is controlled to execute the emergency inspection task.

5. The method for determining the inspection sequence of drones according to any one of claims 1 to 3, characterized in that: The method further comprises: Before the UAV performs inspection tasks in sequence according to the task level, it determines whether there is a time-sensitive task with a fixed task start time; After the time-sensitive task exists and the drone performs inspection according to the inspection order, the drone is controlled to suspend execution of the current inspection task at the fixed task start time, and execute the time-sensitive task according to the fixed task start time.

6. The method for determining the inspection sequence of drones according to claim 1, characterized in that: The method of determining the inspection order of the UAV when performing inspection tasks of the same mission level according to the optimal order of all includes: Select any target inspection area closest to the airport of the drone from all target inspection areas; With the airport of the drone as the center of the circle, determine the arrangement order of all target inspection areas in the preset direction; The inspection sequence is determined according to the optimal sequence of each target inspection area in the arrangement sequence.

7. A device for determining the inspection sequence of drones, characterized in that: The device comprises: a memory configured to store instructions; A processor is configured to call the instructions from the memory and implement the method for determining the inspection order of a drone according to any one of claims 1 to 6 when executing the instructions.

8. A mine inspection system, characterized in that: include: UAVs are used to perform inspection tasks within the mining area, including mine slope inspection tasks, production inspection tasks, pre-blasting inspection tasks, and dam body inspection tasks; a charging device, used to supply power to the drone; The device for determining the inspection sequence of drones according to claim 7.

9. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to perform the method for determining the inspection order of a drone according to any one of claims 1 to 6.

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