Unmanned aerial vehicle road inspection deployment method and related device

Abstract

The embodiment of the invention relates to the field of data processing and unmanned aerial vehicle deployment, and provides an unmanned aerial vehicle road inspection deployment method and a related device, and the method comprises the steps: obtaining the side slope information of a to-be-inspected road, and obtaining the cruise duration information of an unmanned aerial vehicle; according to the side slope information, the forced division points and the cruise duration information, determining the number of unmanned aerial vehicles when the to-be-inspected road is inspected; according to the slope information, performing optimization solving on the unmanned aerial vehicle deployment position to obtain unmanned aerial vehicle deployment position information; the unmanned aerial vehicles are deployed by adopting the unmanned aerial vehicle deployment position information and the number of the unmanned aerial vehicles, the number and the deployment positions of the inspection unmanned aerial vehicles can be determined by combining the slope information of the road to be inspected, the forced division points, the cruise duration information and the like, and finally deployment is performed, so that the accuracy of unmanned aerial vehicle deployment is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing and unmanned aerial vehicle deployment, in particular to an unmanned aerial vehicle road inspection deployment method and related device. BACKGROUND

[0002] When performing road inspection, the existing scheme usually adopts manual inspection to perform inspection, and uses the manual inspection result to perform early warning discrimination. In some special road sections, manual inspection is greatly limited due to the particularity of the road, for example, performing inspection on a highway. At this time, some automatic inspection equipment is used to perform inspection, for example, using an unmanned aerial vehicle to perform inspection. Due to the limitations of endurance and position, the accuracy of the existing unmanned aerial vehicle inspection scheme is low when performing inspection deployment. SUMMARY

[0003] Embodiments of the present application provide an unmanned aerial vehicle road inspection deployment method and related device, which can determine the number and deployment position of the inspection unmanned aerial vehicle by combining the slope information, forced division point and cruise time information of the road to be inspected, and finally perform deployment, thereby improving the accuracy of the unmanned aerial vehicle deployment.

[0004] A first aspect of embodiments of the present application provides an unmanned aerial vehicle road inspection deployment method, which comprises: obtaining slope information of a road to be inspected, and obtaining cruise time information of an unmanned aerial vehicle; determining the number of unmanned aerial vehicles when performing inspection on the road to be inspected according to the slope information, forced division point and cruise time information; performing optimization and solution on the unmanned aerial vehicle deployment position according to the slope information to obtain unmanned aerial vehicle deployment position information; performing unmanned aerial vehicle deployment using the unmanned aerial vehicle deployment position information and the number of unmanned aerial vehicles.

[0005] In one possible implementation, the determination of the number of unmanned aerial vehicles when performing inspection on the road to be inspected according to the slope information, forced division point and cruise time information comprises: constructing a key point sequence of the road to be inspected according to the slope information and forced division point to obtain a first key point sequence; performing time constraint construction according to the first key point sequence and cruise time information to obtain total time constraint; confirming the number of unmanned aerial vehicles by traversing a starting point set for the key points in the first key point sequence under the condition of meeting the total time constraint, to obtain the number of unmanned aerial vehicles when performing inspection on the road to be inspected.

[0006] In one possible implementation, the performance of time constraint construction according to the first key point sequence and cruise time information to obtain total time constraint comprises: The total time constraint is obtained by using the method shown in the following formula: ; Wherein, X i is the i-th key point, X j is the j-th key point, j is less than i, the value range of i is [0, m], m is the total number of slopes, v is the flight speed of the UAV, tk is the inspection time, xk is the position between the j-th key point and the i-th key point, and T is the cruise duration information.

[0007] In one possible implementation, the UAV deployment position is optimized and solved according to the slope information, and the UAV deployment position information is obtained, including: The UAV deployment position information is obtained by optimizing and solving according to the following formula: ; Wherein, y is the UAV deployment position, x i is the i-th slope position, and m is the total number of slopes.

[0008] In one possible implementation, the UAV deployment position is optimized and solved according to the slope information, and the UAV deployment position information is obtained, including: The UAV deployment position information is obtained by optimizing and solving according to the following formula: ; Wherein, y is the UAV deployment position, , is the slope coordinate of the jurisdiction area of the UAV deployment.

[0009] The second aspect of the embodiment of the application provides a UAV road inspection deployment device, and the device comprises: An acquisition unit is configured to acquire slope information of a road to be inspected and cruise duration information of a UAV; A determination unit is configured to determine a number of UAVs for inspecting the road to be inspected according to the slope information, the forced division point and the cruise duration information; A solving unit is configured to optimize and solve a UAV deployment position according to the slope information, and obtain UAV deployment position information; A deployment unit is configured to deploy the UAV according to the UAV deployment position information and the number of UAVs.

[0010] In one possible implementation, the determination unit is specifically configured to: construct a key point sequence according to the slope information and the forced division point, and obtain a first key point sequence; constructing a total time constraint according to the first key point sequence and the cruise time length information; confirming the number of unmanned aerial vehicles according to the first key point sequence and the total time constraint, to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected.

[0011] In one possible implementation, in the aspect of constructing the total time constraint according to the first key point sequence and the cruise time length information, the determining unit is specifically configured to: construct the total time constraint by using a method shown in the following formula: ; wherein, X i is the ith key point, X j is the jth key point, j is less than i, the value range of i is [0, m], m is the total number of slopes, v is the flight speed of the unmanned aerial vehicle, tk is the inspection time, xk is the position between the jth key point and the ith key point, and T is the cruise time length information.

[0012] In one possible implementation, the solving unit is specifically configured to: obtain the unmanned aerial vehicle deployment position information by using a method shown in the following formula: ; wherein, y is the unmanned aerial vehicle deployment position, x i is the ith slope position, and m is the total number of slopes.

[0013] In one possible implementation, the solving unit is specifically configured to: obtain the unmanned aerial vehicle deployment position information by using a method shown in the following formula: ; wherein, y is the unmanned aerial vehicle deployment position, , is the slope coordinate of the jurisdiction area of the unmanned aerial vehicle deployment.

[0014] A third aspect of the embodiment of the application provides a terminal, including a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are connected with each other, wherein the memory is used for storing a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions and execute the step instructions in the first aspect of the embodiment of the application.

[0015] A fourth aspect of the embodiments of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program for electronic data exchange, and the computer program causes a computer to perform some or all of the steps described in the first aspect of the embodiments of the present application.

[0016] A fifth aspect of the embodiments of the present application provides a computer program product, which includes a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application. The computer program product can be a software installation package.

[0017] The embodiments of the present application have the following beneficial effects: By acquiring the slope information of the road to be inspected and the cruising time information of the unmanned aerial vehicle, the number of unmanned aerial vehicles for inspecting the road to be inspected is determined according to the slope information, the forced division point and the cruising time information, the unmanned aerial vehicle deployment position is optimized and solved according to the slope information, the unmanned aerial vehicle deployment position information is obtained, and the unmanned aerial vehicle deployment position information and the number of unmanned aerial vehicles are used for unmanned aerial vehicle deployment. Therefore, the number and deployment position of the inspection unmanned aerial vehicle can be determined by combining the slope information, the forced division point and the cruising time information of the road to be inspected, and finally deployed, thereby improving the accuracy of unmanned aerial vehicle deployment. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0019] Figure 1 A flowchart of a method for deploying an unmanned aerial vehicle for road inspection is provided for the embodiments of the present application; Figure 2 A structural diagram of a terminal is provided for the embodiments of the present application; Figure 3 A structural diagram of an unmanned aerial vehicle road inspection deployment device is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0020] With reference to the drawings and briefly describing the technical solutions in the embodiments of the present application, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0021] The terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or device.

[0022] In the present application, "embodiment" means that the specific features, structures, or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment to other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments.

[0023] In order to better understand the unmanned aerial vehicle road inspection deployment method provided by the embodiments of the present application, first, the road inspection method in the prior art will be briefly introduced. In the prior art, manual inspection is usually used for inspection, and the results of manual inspection are used for early warning discrimination. In some special road sections, manual inspection is greatly limited due to the particularity of the road, for example, inspection of expressway. At this time, some automatic inspection equipment is used for inspection, for example, unmanned aerial vehicle is used for inspection. In the existing unmanned aerial vehicle inspection scheme, due to the limitation of endurance, position, etc., the accuracy of the inspection deployment is low.

[0024] To solve the above problems, the embodiments of the present application provide an unmanned aerial vehicle road inspection deployment method, which can determine the number and deployment position of the inspection unmanned aerial vehicle by combining the slope information, forced division point and cruise time information of the road to be inspected, and finally deploy, thereby improving the accuracy of the unmanned aerial vehicle deployment.

[0025] Please refer to Figure 1 , Figure 1 A flowchart of the unmanned aerial vehicle road inspection deployment method provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the method comprises the following steps. Figure 1 ​101. Obtain slope information of the road to be inspected, and obtain information on the drone's patrol duration.

[0026] The slope information includes its location and area. Cruise duration information can be understood as the maximum operating time of the drone during a cruise. Maximum operating time can include both flight time and inspection time. Flight time includes the total round-trip flight time.

[0027] 102. Determine the number of drones to be inspected for the road based on the slope information, forced division points, and cruise duration information.

[0028] Specifically, in one possible implementation, determining the number of drones for inspecting the road based on the slope information, forced demarcation points, and cruise duration information includes: A1. Based on the slope information and the forced division points, construct the key point sequence of the road to be inspected to obtain the first key point sequence; A2. Construct time constraints based on the first key point sequence and cruise duration information to obtain the total time constraints; A3. Under the condition of satisfying the total time constraint, the number of drones is confirmed by traversing the starting set of key points in the first key point sequence, so as to obtain the number of drones when inspecting the road to be inspected.

[0029] It can be every D max Kilometer insertion forced partition points (e.g., 0, D) max 2D max , ...).

[0030] After merging the start point, end point, slope location, and forced division points of the road to be inspected, and sorting them, the first key point sequence X=[X0, X1, ..., X...] is obtained. m ], where X0=0, X m =L, where L is the length of the road to be inspected.

[0031] For example, the time constraints can be constructed using the method shown in the following formula to obtain the total time constraints: ; Among them, X i For the i-th key point, X j Let j be the j-th key point, j is less than i, i is in the range of [0, m], m is the total number of slopes, v is the flight speed of the UAV, tk is the inspection time, xk is the position between the j-th key point and the i-th key point, and T is the cruise duration information.

[0032] Under the satisfaction of the total time constraint, the confirmation of the number of unmanned aerial vehicles is performed for the key points in the first key point sequence, and the number of unmanned aerial vehicles for the inspection of the to-be-inspected road can be specifically: ; Among them, is the minimum number of unmanned aerial vehicles (the number of inspection unmanned aerial vehicles) required to cover the key point X i , in the initialization state, , the rest .

[0033] 103. Optimize and solve the unmanned aerial vehicle deployment position according to the slope information to obtain the unmanned aerial vehicle deployment position information.

[0034] In one possible implementation, since the slope is a point with high risk and great influence, the shortest total time method of deploying unmanned aerial vehicles to the jurisdictional slope in each section is adopted. Specifically, a method for optimizing and solving the unmanned aerial vehicle deployment position according to the slope information to obtain the unmanned aerial vehicle deployment position information, comprising: Optimize and solve the unmanned aerial vehicle deployment position according to the slope information to obtain the unmanned aerial vehicle deployment position information by the following formula: ; Among them, y is the unmanned aerial vehicle deployment position, x i is the i-th slope position, m is the total number of slopes, and the one-dimensional space solution is: y = median (x1, x2, …, x m ).

[0035] In this example, by obtaining the slope information of the to-be-inspected road and the cruising time information of the unmanned aerial vehicle, the number of unmanned aerial vehicles for the inspection of the to-be-inspected road is determined according to the slope information, the forced division point and the cruising time information, the unmanned aerial vehicle deployment position is optimized and solved according to the slope information to obtain the unmanned aerial vehicle deployment position information, and the unmanned aerial vehicle deployment position information and the number of unmanned aerial vehicles are used for unmanned aerial vehicle deployment. Therefore, the number and deployment position of the inspection unmanned aerial vehicle can be determined in combination with the slope information, the forced division point and the cruising time information of the to-be-inspected road, and finally deployed, thereby improving the accuracy of the unmanned aerial vehicle deployment.

[0036] In one specific implementation, the present application embodiment provides a specific unmanned aerial vehicle road inspection deployment method, which is specifically as follows: Assume that the to-be-inspected road length L = 100 kilometers; Slope position: x = [5, 15, 30, 45, 60, 65, 70, 80, 90, 95] km.

[0037] The inspection time t of each slope is [10, 15, 20, 10, 5, 10, 15, 20, 10, 5] minutes; UAV parameters: flight speed v = 1 km / min, endurance time T = 120 minutes Then the maximum one-way distance is: ; Forced division points: insert forced division points every 60 kilometers, that is, 0 60 kilometers 120 kilometers (since the length is 100 kilometers, the actual forced division point is 0 60 kilometers).

[0038] Merge the highway endpoints, slope positions, and forced division points, and sort them to get: X = [0, 5, 15, 30, 45, 60, 65, 70, 80, 90, 95, 100] 1. The minimum number of UAVs deployed to cover the entire highway: 1.1 Interval [0, 60] Slope position: 5, 15, 30, 45, 60; Total inspection time: 10 + 15 + 20 + 10 + 5 = 60 minutes; Round-trip flight time: 120 minutes; Total time: 120 + 60 = 180 > T (not feasible); Split strategy: the interval needs to be split into smaller intervals; 1.2 Interval [0, 30] Slope position: 5, 15, 30; Total inspection time: 10 + 15 + 20 = 45 minutes; Round-trip flight time: 60 minutes; Total time: 60 + 45 = 105 < T; Farthest time: 15 minutes 1.3 Interval [30, 60] Slope position: 45, 60; Total inspection time: 10 + 5 = 15 minutes; Round-trip flight time: 60 minutes; Total time: 60 + 15 = 75 ≤ T; Farthest time: 15 minutes.

[0039] 1.4 Interval [60, 90] Slope position: 65, 70, 80, 90; The total inspection time is 10+15+20+10=55 minutes. The round-trip flight time is 60 minutes. The total time is 60+55=115<T. The farthest time is 15 minutes 1.5 interval [90,100] The slope position is 95; The total inspection time is 5 minutes. The round-trip flight time is 20 minutes. The total time is 20+5=25<T. The farthest time is 5 minutes.

[0040] Finally, 4 drones are determined, and the jurisdiction ranges are [0,30] (30,60] (60,90] (90,100] respectively.

[0041] (1) When the number of drones is determined to be 4, because the slope is a point with high risk and great impact, the shortest total time of each section drone to the jurisdiction slope is used for deployment: (2) When the number of drones is determined to be 4, because the slope is a point with high risk and great impact, in order to ensure that the drone can arrive at the scene in the first time, the shortest time of each section drone to the farthest slope in the jurisdiction area is used for deployment: The deployment position of the drone , wherein , is the coordinate of the slope at both ends of the jurisdiction area of the drone deployment.

[0042] For the above embodiment, please refer to Figure 2 , Figure 2 is a structural schematic diagram of a terminal provided by the embodiment of the present application, as Figure 2 shown, including a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are connected with each other, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, the above program includes instructions for executing the following steps; Obtain the slope information of the road to be inspected, and obtain the cruise time information of the drone; Determine the number of drones for inspecting the road to be inspected according to the slope information, the forced division point and the cruise time information; solving the position of the UAV deployment according to the slope information to obtain UAV deployment position information; deploying the UAVs according to the UAV deployment position information and the number of UAVs.

[0043] The above mainly introduces the scheme of the embodiments of the present application from the perspective of the process of executing the method. It can be understood that the terminal contains the hardware structure and / or software module corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily realize that, in combination with the unit and algorithm steps of each example described in the embodiments provided herein, the present application can be realized in the form of hardware or the combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. The professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0044] The embodiments of the present application can divide the functional units of the terminal according to the above method examples. For example, each functional unit can be divided according to each function, or two or more functions can be integrated in one processing unit. The integrated unit can be realized in the form of hardware or software functional unit. It should be noted that the division of units in the embodiments of the present application is illustrative, and is only a logical function division. There can be another division method in actual implementation.

[0045] Consistent with the above, please refer to Figure 3 , Figure 3 The embodiments of the present application provide a structural schematic diagram of a UAV road inspection deployment device. As shown in Figure 3 , the device comprises: The acquisition unit 301 is configured to acquire slope information of a road to be inspected and cruise duration information of a UAV. The determination unit 302 is configured to determine the number of UAVs for inspecting the road to be inspected according to the slope information, the forced division point and the cruise duration information. The solving unit 303 is configured to solve the position of the UAV deployment according to the slope information to obtain UAV deployment position information. The deployment unit 304 is configured to deploy the UAVs according to the UAV deployment position information and the number of UAVs.

[0046] In one possible implementation, the determination unit 302 is specifically configured to: construct a key point sequence according to the slope information and the forced division point to obtain a first key point sequence; According to the first key point sequence and the cruise time length information, total time constraints are constructed. Under the total time constraints, the number of UAVs is confirmed by traversing the starting point set of the key points in the first key point sequence, and the number of UAVs for inspecting the road to be inspected is obtained.

[0047] In one possible implementation, in the aspect of constructing the total time constraints according to the first key point sequence and the cruise time length information, the determining unit 302 is specifically configured to: The total time constraints are constructed by using a method shown in the following formula: ; wherein, X i is the i-th key point, X j is the j-th key point, j is less than i, the value range of i is [0, m], m is the total number of slopes, v is the flight speed of the UAV, tk is the inspection time, xk is the position between the j-th key point and the i-th key point, and T is the cruise time length information.

[0048] In one possible implementation, the solving unit 303 is specifically configured to: The UAV deployment position information is obtained by using a method shown in the following formula: ; wherein, y is the UAV deployment position, x i is the i-th slope position, and m is the total number of slopes.

[0049] In one possible implementation, the solving unit 303 is specifically configured to: The UAV deployment position information is obtained by using a method shown in the following formula: ; wherein, y is the UAV deployment position, , is the slope coordinate of the two ends of the jurisdiction area of the UAV deployment.

[0050] The embodiment of the application further provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program causes the computer to execute part or all steps of any one of the UAV road inspection deployment methods described in the above method embodiments.

[0051] The embodiment of the present application further provides a computer program product, which comprises a non-transitory computer-readable storage medium storing a computer program, and the computer program causes a computer to execute some or all of the steps of any of the UAV road inspection deployment methods described in the above method embodiments.

[0052] It should be noted that, for the above-mentioned method embodiments, in order to simply describe, they are all described as a combination of a series of actions, but those skilled in the art should know that the present application is not limited to the action sequence described, because according to the present application, some steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0053] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0054] In several embodiments provided in the present application, it should be understood that the disclosed apparatus can be implemented by other means. For example, the apparatus embodiments described above are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, apparatus or unit, and can be electrical or other forms.

[0055] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0056] In addition, the functional units in each embodiment of the application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software program module.

[0057] If the integrated unit is realized in the form of a software program module and sold or used as an independent product, it can be stored in a computer readable memory. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0058] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer readable memory, which can include a flash disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0059] The embodiments of the present application are described in detail above, and the principles and implementation manners of the present application are described by applying specific examples. The above description of the embodiments is only used to help understand the method of the present application and its core idea; meanwhile, for those of ordinary skill in the art, according to the idea of the present application, the specific implementation manner and application range will be changed, and the above description of the embodiments should not be understood as a limitation of the present application.

Claims

1. A method for deploying unmanned aerial vehicles (UAVs) for road inspection, characterized in that, The method comprises: Obtain the slope information of the road to be inspected, and obtain the cruise time information of the unmanned aerial vehicle; Determine the number of unmanned aerial vehicles for inspecting the road to be inspected according to the slope information, the forced division point and the cruise time information; Optimize and solve the deployment position of the unmanned aerial vehicle according to the slope information to obtain the deployment position information of the unmanned aerial vehicle; Deploy the unmanned aerial vehicle by using the deployment position information of the unmanned aerial vehicle and the number of unmanned aerial vehicles.

2. The method of claim 1, wherein, The method comprises: According to the slope information and the forced division point, a key point sequence of the road to be inspected is constructed to obtain a first key point sequence; According to the first key point sequence and the cruise time information, time constraints are constructed to obtain total time constraints; Under the condition of meeting the total time constraints, the number of unmanned aerial vehicles is confirmed by traversing the starting point set for the key points in the first key point sequence to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected. 3.The method of claim 2, wherein, The method comprises: According to the slope information and the forced division point, a key point sequence of the road to be inspected is constructed to obtain a first key point sequence; ； wherein X i is the i-th key point, X j is the j-th key point, j is less than i, i has a value range of [0, m], m is the total number of slopes, v is the flight speed of the UAV, tk is the inspection time, xk is the position between the j-th key point and the i-th key point, and T is the cruise duration information.

4. The method of claim 2 or 3, wherein, According to the first key point sequence and the cruise time information, time constraints are constructed to obtain total time constraints; Under the condition of meeting the total time constraints, the number of unmanned aerial vehicles is confirmed by traversing the starting point set for the key points in the first key point sequence to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected. ； Wherein, y is the deployment position of the unmanned aerial vehicle, x i is the i-th slope position, and m is the total number of slopes.

5. The method of claim 2 or 3, wherein, The method comprises: According to the slope information and the forced division point, a key point sequence of the road to be inspected is constructed to obtain a first key point sequence; ； Wherein, y is the unmanned aerial vehicle deployment position, , is the slope coordinate of the two ends of the unmanned aerial vehicle deployment jurisdiction area.

6. An unmanned aerial vehicle road inspection deployment device, characterized in that, According to the first key point sequence and the cruise time information, time constraints are constructed to obtain total time constraints; Under the condition of meeting the total time constraints, the number of unmanned aerial vehicles is confirmed by traversing the starting point set for the key points in the first key point sequence to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected. The device comprises: An acquisition unit is configured to acquire the slope information of the road to be inspected, and acquire the cruise time information of the unmanned aerial vehicle; A determination unit is configured to determine the number of unmanned aerial vehicles for inspecting the road to be inspected according to the slope information, the forced division point and the cruise time information; 7. The unmanned aerial vehicle road inspection deployment apparatus of claim 6, wherein, A solving unit is configured to optimize and solve the deployment position of the unmanned aerial vehicle according to the slope information to obtain the deployment position information of the unmanned aerial vehicle; A deployment unit is configured to deploy the unmanned aerial vehicle by using the deployment position information of the unmanned aerial vehicle and the number of unmanned aerial vehicles. The determination unit is specifically configured to: According to the slope information and the forced division point, a key point sequence of the road to be inspected is constructed to obtain a first key point sequence; 8.The method of claim 7, wherein, According to the first key point sequence and the cruise time information, time constraints are constructed to obtain total time constraints; Under the condition of meeting the total time constraints, the number of unmanned aerial vehicles is confirmed by traversing the starting point set for the key points in the first key point sequence to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected. In terms of constructing the total time constraints according to the first key point sequence and the cruise time information, the determination unit is specifically configured to: According to the slope information and the forced division point, a key point sequence of the road to be inspected is constructed to obtain a first key point sequence; According to the first key point sequence and the cruise time information, time constraints are constructed to obtain total time constraints; Under the condition of meeting the total time constraints, the number of unmanned aerial vehicles is confirmed by traversing the starting point set for the key points in the first key point sequence to obtain the number of unmanned aerial vehicles for inspecting the road to be inspected. ； wherein X i is the i-th key point, X j is the j-th key point, j is less than i, i is in the range of [0, m], m is the total number of slopes, v is the flight speed of the UAV, tk is the inspection time, xk is the position between the j-th key point and the i-th key point, and T is the cruise duration information.

9. A terminal, characterized by comprising: The computer readable storage medium stores a computer program, and the computer program includes program instructions. The program instructions, when executed by a processor, cause the processor to perform the method for deploying a UAV for road inspection according to any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program includes program instructions. The program instructions, when executed by a processor, cause the processor to perform the method for deploying a UAV for road inspection according to any one of claims 1-5.

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