Unmanned aerial vehicle route construction method and related device

Abstract

The embodiment of the invention relates to the technical field of unmanned aerial vehicle route planning, and provides an unmanned aerial vehicle route construction method and a related device, and the method comprises the steps: obtaining unmanned aerial vehicle inspection task data and an unmanned aerial vehicle route database; according to the unmanned aerial vehicle inspection task data, determining an unmanned aerial vehicle waypoint inspection sequence; extracting an original unmanned aerial vehicle route inspection sequence from the unmanned aerial vehicle route database, and comparing the original unmanned aerial vehicle route inspection sequence with the unmanned aerial vehicle waypoint inspection sequence to obtain an unmanned aerial vehicle waypoint inspection sequence comparison result; according to the unmanned aerial vehicle waypoint inspection sequence comparison result, the unmanned aerial vehicle route is planned, the unmanned aerial vehicle inspection route is obtained, original data in an unmanned aerial vehicle route database can be fully utilized, the real-time inspection task requirement is combined, and more efficient and accurate unmanned aerial vehicle route planning is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of unmanned aerial vehicle (UAV) route planning, and in particular to a method for constructing an UAV route and related devices. Background Art

[0002] In drone inspection operations, path planning is a key step to ensure that drones can complete inspection tasks efficiently and safely. Drone path planning refers to the process of determining the optimal flight path for drones from a starting point to a target point in a given environment through a series of algorithms and techniques. This process is designed to ensure that drones can complete flight missions efficiently and safely, while avoiding obstacles and other aircraft, and meeting specific flight requirements.

[0003] Traditional UAV path planning methods mostly rely on point cloud data collected in real time by inspection equipment. These data are processed and analyzed through algorithms to generate flight paths. Direct path planning based on point cloud data often requires real-time processing of large amounts of data, which not only increases the computational complexity but may also lead to inefficient planning. Summary of the invention

[0004] The embodiments of the present application provide a method and related devices for constructing a UAV route, which fully utilizes the original data in the UAV route database and combines it with real-time inspection task requirements to achieve more efficient and accurate UAV path planning.

[0005] A first aspect of an embodiment of the present application provides a method for constructing a drone route, the method comprising:

[0006] Obtain drone inspection mission data and drone route database;

[0007] According to the UAV inspection task data, confirm the UAV waypoint inspection sequence;

[0008] Extracting an original drone route inspection sequence from the drone route database, comparing the original drone route inspection sequence with the drone waypoint inspection sequence, and obtaining a drone waypoint inspection sequence comparison result;

[0009] According to the comparison result of the inspection sequence of the UAV waypoints, the UAV route is planned to obtain the UAV inspection route.

[0010] Further, the determining of the drone waypoint inspection sequence according to the drone inspection task data and the drone route database includes:

[0011] According to the drone inspection mission data, extract corresponding safety channel route data and waypoint data from the drone route database;

[0012] According to the safety channel route data and waypoint data, confirm the drone route starting entry point, n intermediate waypoints, and the drone route ending safety point;

[0013] According to the starting safety point of the human-machine route, n intermediate waypoints and the ending safety point of the drone route, the inspection sequence of the drone waypoints is confirmed.

[0014] Further, the step of confirming the starting entry point of the drone route according to the safe channel route data and waypoint data includes:

[0015] According to the safety channel route data and the waypoint data, sequentially calculating the waypoints and distances closest to the waypoints in the safety channel route;

[0016] Select the first waypoint corresponding to the smallest distance as the starting safety point of the drone route;

[0017] According to the starting safety point of the UAV route, confirm the second waypoint where the UAV leaves the safety channel for inspection at the beginning of the route;

[0018] According to the second waypoint, the third waypoint closest to the safety channel where the second waypoint is located is selected and confirmed as the starting entry point of the drone route.

[0019] Further, the step of confirming the inspection sequence of the drone waypoints according to the starting safety point of the drone route, the n intermediate waypoints and the ending safety point of the drone route includes:

[0020] According to the starting safety point of the UAV route, n intermediate waypoints and the ending safety point of the UAV route, the Google ortools solver is used to perform the shortest path planning to obtain the UAV waypoint inspection sequence.

[0021] Furthermore, the planning of the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route includes:

[0022] If the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part;

[0023] If the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, the improved RRT algorithm is used to plan the route that does not overlap at all or partially overlaps with the original UAV route to obtain the route as the UAV planned route for the non-overlapping part;

[0024] The planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts are spliced ​​to obtain the UAV inspection route.

[0025] In this example, the inspection order of the drone inspection task is first determined based on the current drone inspection task to be executed, and the inspection order of the drone inspection task is compared with the original drone inspection route in the database. The original drone inspection route is used to plan the current drone inspection route based on the comparison results, which can reduce the amount of data processing, not only improve planning efficiency, but also optimize the flight path.

[0026] A second aspect of an embodiment of the present application provides a drone route construction device, the device comprising:

[0027] An acquisition unit, used to acquire UAV inspection mission data and UAV route database;

[0028] A first processing unit is used to confirm the inspection sequence of the drone waypoints according to the drone inspection task data;

[0029] A second processing unit is used to extract an original drone route inspection sequence from the drone route database, compare the original drone route inspection sequence with the drone waypoint inspection sequence, and obtain a drone waypoint inspection sequence comparison result;

[0030] The third processing unit is used to plan the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route.

[0031] Further, in the aspect of confirming the inspection sequence of the drone waypoints according to the drone inspection task data, the first processing unit is used to:

[0032] According to the drone inspection mission data, extract corresponding safety channel route data and waypoint data from the drone route database;

[0033] According to the safety channel route data and waypoint data, confirm the drone route starting entry point, n intermediate waypoints, and the drone route ending safety point;

[0034] According to the starting safety point of the human-machine route, n intermediate waypoints and the ending safety point of the drone route, the inspection sequence of the drone waypoints is confirmed.

[0035] Further, in the aspect of confirming the inspection sequence of the drone waypoints according to the starting safety point of the drone route, the n intermediate waypoints and the ending safety point of the drone route, the first processing unit is used to:

[0036] According to the starting safety point of the UAV route, n intermediate waypoints and the ending safety point of the UAV route, the Google ortools solver is used to perform the shortest path planning to obtain the UAV waypoint inspection sequence.

[0037] Further, in confirming the starting entry point of the drone route according to the safety channel route data and the waypoint data, the first processing unit is used to:

[0038] According to the safety channel route data and the waypoint data, sequentially calculating the waypoints and distances closest to the waypoints in the safety channel route;

[0039] Select the first waypoint corresponding to the smallest distance as the starting safety point of the drone route;

[0040] According to the starting safety point of the UAV route, confirm the second waypoint where the UAV leaves the safety channel for inspection at the beginning of the route;

[0041] According to the second waypoint, the third waypoint closest to the safety channel where the second waypoint is located is selected and confirmed as the starting entry point of the drone route.

[0042] Further, in the step of planning the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route, the third processing unit is used to:

[0043] If the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part;

[0044] If the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, the improved RRT algorithm is used to plan the route that does not overlap at all or partially overlaps with the original UAV route to obtain the route as the UAV planned route for the non-overlapping part;

[0045] The planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts are spliced ​​to obtain the UAV inspection route.

[0046] A third aspect of an embodiment of the present application provides a terminal, comprising a processor, an input device, an output device and a memory, wherein the processor, input device, output device and memory are interconnected, wherein the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the step instructions of the drone route construction method in the first aspect of the embodiment of the present application.

[0047] The fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the above-mentioned computer-readable storage medium stores a computer program for electronic data exchange, wherein the above-mentioned computer program enables the computer to execute part or all of the steps described in the drone route construction method in the first aspect of the embodiment of the present application.

[0048] A fifth aspect of the embodiments of the present application provides a computer program product, wherein the computer program product 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 method for constructing a drone route in the first aspect of the embodiments of the present application. The computer program product may be a software installation package. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A schematic diagram of the overall process of a method for constructing a drone route is provided for an embodiment of the present application;

[0051] Figure 2 A schematic diagram of confirming the starting entry point of a drone route in a method for constructing a drone route is provided for an embodiment of the present application;

[0052] Figure 3 A schematic diagram of the structure of a UAV route construction device is provided for an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of the present application;

[0054] Figure 5 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 1 ;

[0055] Figure 6 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 2 ;

[0056] Figure 7A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 3 ;

[0057] Figure 8 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 4 ;

[0058] Fig. 9 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 5 ;

[0059] Fig.10 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 6 ;

[0060] Fig.11 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 7 ;

[0061] Fig.12 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 8 ;

[0062] Fig.13 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 9 ;

[0063] Fig.14 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 ;

[0064] Fig.15 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 one;

[0065] Fig.16 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10two;

[0066] Fig.17 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 three;

[0067] Fig.18 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 Four;

[0068] Fig.19 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 five;

[0069] Fig. 20 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 six;

[0070] Fig.21 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 seven;

[0071] Fig. 22 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 eight;

[0072] Fig.23 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a route for a drone is provided in an embodiment of the present application. Figure 10 Nine;

[0073] Reference numerals:

[0074] Acquisition unit-1, first processing unit-2, second processing unit-3, third processing unit-4. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0076] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0077] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0078] In order to better understand the UAV route construction method provided by the embodiment of the present application, the following first briefly introduces the scenario of applying the UAV route construction method. In the process of planning traditional UAV routes, it is often based on the point cloud data collected in real time by the inspection equipment. The algorithm directly processes and analyzes a large amount of data in real time based on the point cloud data to generate a flight path. Not only does it not use the original data in the UAV route database, but the efficiency of route planning is slow due to the large amount of data processing and calculation.

[0079] The UAV route construction method is applied to the UAV route construction device. Figure 1 The overall process diagram of a method for constructing a UAV route is shown in FIG. Figure 1 As shown, including:

[0080] S1. Obtain UAV inspection task data and UAV route database, where the UAV route database includes point cloud data of all inspected substations and original UAV route data, that is, previously planned UAV route data, and the point cloud data is converted into a Gaussian coordinate system, and the x, y, z coordinates are indexed, which can be quickly retrieved.

[0081] S2. According to the UAV inspection task data, confirm the UAV waypoint inspection sequence, specifically including:

[0082] S201. Extract corresponding safety channel route data and waypoint data from the drone route database according to the drone inspection mission data.

[0083] S202: confirm the drone route starting entry point, n intermediate waypoints, and drone route ending safety point based on the safety channel route data and waypoint data.

[0084] In this example, Figure 2 The schematic diagram of the confirmation of the starting entry point of the drone route is shown. The specific steps of confirming the starting entry point of the drone route include:

[0085] S2021. According to the safety channel route data and waypoint data, the waypoints and distances closest to the waypoints in the safety channel route are calculated in sequence.

[0086] S2022: Select the first waypoint corresponding to the minimum distance as the starting safety point of the drone route.

[0087] S2023. According to the starting safety point of the UAV route, confirm the second waypoint where the UAV leaves the safety channel to perform inspection operations at the beginning of the route.

[0088] S2024. According to the second waypoint, select the third waypoint closest to the safety passage where the second waypoint is located and confirm it as the starting entry point of the drone route.

[0089] The specific steps for confirming the intermediate waypoints include: for the waypoints to be inspected, the Google ortools solver is used for shortest path planning, where the starting point is set as the starting safety point, and any inspection waypoint in the middle is used as the intermediate waypoint, including n intermediate waypoints.

[0090] The specific steps of the drone route end safety point include: selecting the last waypoint of the waypoint sequence obtained in the previous step, similar to the method of finding the starting safety point, finding the nearest waypoint of the safety channel closest to the last waypoint as the end safety point of the inspection work, and then calculating the endpoint closest to the safety point on the safety channel as the end point of the entire track.

[0091] S203. Confirm the inspection order of the drone waypoints according to the starting safety point of the man-machine route, the n intermediate waypoints and the ending safety point of the drone route. Since the starting safety point of the man-machine route, the n intermediate waypoints and the ending safety point of the drone route are all confirmed, the inspection order of the drone waypoints is therefore confirmed.

[0092] S3. Extracting the original drone route inspection sequence from the drone route database, comparing the original drone route inspection sequence with the drone waypoint inspection sequence, and obtaining a drone waypoint inspection sequence comparison result, specifically including:

[0093] S301A, if the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part;

[0094] S301B, if the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, use the improved RRT algorithm to plan a route that does not overlap at all or partially overlaps with the original UAV route to obtain a route as the UAV planned route for the non-overlapping portion;

[0095] S302: splice the planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts to obtain the UAV inspection routes.

[0096] S4. According to the comparison result of the inspection sequence of the UAV waypoints, the UAV route is planned to obtain the UAV inspection route. At this point, a complete UAV inspection route can be obtained, including: UAV entry point -> starting safety point -> inspection point 1 -> inspection point 2 -> ... -> inspection point n -> end safety point -> track end point.

[0097] In this example, the inspection order of the drone inspection task is first determined based on the current drone inspection task to be executed, and the inspection order of the drone inspection task is compared with the original drone inspection route in the database. The original drone inspection route is used to plan the current drone inspection route based on the comparison results, which can reduce the amount of data processing, not only improve planning efficiency, but also optimize the flight path.

[0098] Further planning is required for the flight paths between inspection waypoints.

[0099] Select each inspection waypoint interval, such as inspection point 1->inspection point 2, and first match it with the original route. If inspection point 1 and inspection point 2 are already continuous waypoints in the original route, no additional route planning is done in this waypoint interval, and the two inspection points can be directly connected. If inspection point 1 and inspection point 2 are not continuous in the original route, track planning is required.

[0100] Before performing track planning, point cloud data must be acquired first. With the line connecting the start and end points of the track interval as the diagonal, a rectangular space can be generated, and then the rectangular space is expanded by a certain distance to obtain the space used for planning. The coordinate data of this space is used to search the database to obtain all the point cloud data in this space. Then, the point cloud data is processed by reducing voxels and deleting outliers to improve planning efficiency.

[0101] In this example, the inspection order of the drone inspection task is first determined based on the current drone inspection task to be executed, and the inspection order of the drone inspection task is compared with the original drone inspection route in the database. The original drone inspection route is used to plan the current drone inspection route based on the comparison results, which can reduce the amount of data processing, not only improve planning efficiency, but also optimize the flight path.

[0102] Implementation process of Voxel Grid Filtering: 1. Voxel grid creation: The method accepts the original point cloud data and voxel size (voxelSize) as input. The voxel size determines the granularity of downsampling. Larger voxel sizes result in coarser but faster downsampling. 2. Points are assigned to voxels: Traverse each point and assign it to the corresponding voxel. Use the VoxelKey class to represent the unique identifier of each voxel, which consists of the x, y, and z indexes of the voxel. The voxel index is calculated by dividing the coordinates of the point by the voxel size and rounding down. 3. Accumulation of points within the voxel: For each voxel, accumulate the coordinates of all the points in it. Use HashMap to store the voxel index (VoxelKey) and the corresponding accumulated coordinates. 4. Calculate the center point of the voxel: Traverse all non-empty voxels. For each voxel, calculate the average coordinates of all the points in it as the representative point of the voxel. 5. Generate the downsampled point cloud: Collect the representative points of all voxels to form a new point cloud dataset. 6. Return result: Return the downsampled point cloud data, usually the number of points will be significantly reduced.

[0103] Implementation process of removing outliers (Statistical Outlier Removal): 1. Initialization: The method accepts the original point cloud data, the number of k nearest neighbors (kNeighbors), and the standard deviation multiplier threshold (stddevMulThresh) as input. 2. Calculate the average distance of each point to its k nearest neighbors: For each point, find its k nearest neighbors. Calculate the average distance from the point to these k neighbors. Store these average distances in a list. 3. Calculate statistics: Use the DescriptiveStatistics class to calculate the mean and standard deviation of all average distances. 4. Filter points: Traverse all points, for each point: if its average distance is less than or equal to (mean + standard deviation multiplier * standard deviation), keep the point. Otherwise, the point is considered an outlier and removed. 5. Return result: Returns the filtered point cloud data, in which the outliers have been removed.

[0104] The trajectory planning algorithm uses the RRT* algorithm. RRT is a fast path planning method that continuously expands the tree through random sampling and is suitable for preliminary path search in complex environments. RRT* is an optimized version of RRT, emphasizing the search for the optimal path and correcting and optimizing the path each time it is expanded.

[0105] The specific steps include:

[0106] 1. Initialization:

[0107] Create a tree with the starting point as the root node.

[0108] 2. Main loop: Repeat the following steps until the maximum number of iterations is reached or the target is found: a) Sampling: Randomly sample a point in the configuration space. b) Find the nearest node: Find the node closest to the sampling point in the tree. c) Expansion: Expand a fixed step from the nearest node in the direction of the sampling point to generate a new node. d) Collision detection: Check whether the new node collides with an obstacle. e) Select parent node: Within a certain radius near the new node, select the node that minimizes the path cost from the starting point to the new node as the parent node. f) Reconnect: Try to use the new node as the parent node and reconnect nearby nodes to optimize the local path. g) Add node: Add the new node and its edges to the tree. h) Check target: If the new node is close enough to the target, the algorithm ends.

[0109] 3. Path extraction:

[0110] Backtrack from the target node to the starting point and extract the final path.

[0111] 3. Key improvements of RRT* Compared with the basic RRT algorithm, RRT* has two major improvements:

[0112] 1. Select the optimal parent node:

[0113] RRT simply connects new nodes to the nearest nodes.

[0114] RRT* selects the node that minimizes the path cost within a certain range as the parent node.

[0115] 2. Reconnect:

[0116] RRT will not modify the existing tree structure.

[0117] RRT* will try to reconnect nearby nodes with new nodes to continuously optimize the tree structure.

[0118] 4. Algorithm characteristics

[0119] Probabilistic completeness: As the number of iterations increases, the probability of finding a path approaches 1.

[0120] Asymptotic optimality: Over time, the algorithm converges to the optimal path.

[0121] Strong adaptability: able to handle high-dimensional spaces and complex environments.

[0122] Computational efficiency: More efficient in high-dimensional spaces than deterministic algorithms.

[0123] 5. Specific process, such as Figure 5-Figure 23 As shown, Figure 5-Figure 23 A specific example of a route obtained by planning a completely non-overlapping or partially non-overlapping route in a method for constructing a UAV route is shown. Figures 1 to 19 ,include:

[0124] 1. Generate a random point xrand.

[0125] 2. Find the node xnearest that is closest to xrand in the tree.

[0126] 3. Connect xrand and xnearest.

[0127] 4. With xrand as the center and ri as the radius, search for nodes on the tree.

[0128] 5. Find the potential parent node set Xpotential_parent, the purpose of which is to update xrand to see if there is a better parent node than it.

[0129] 6. Start considering a potential parent node xpotential_parent.

[0130] 7. Calculate the cost when xparent is the parent node.

[0131] 8. Do not perform collision detection first, but connect xpotential_parent to xchild (that is, xrand).

[0132] 9. Calculate the cost of this path.

[0133] 10. Compare the cost of the new path with the cost of the original path. If the cost of the new path is smaller, perform a collision check. If the cost of the new path is larger, switch to the next potential parent node.

[0134] 11. Collision detection fails and the potential parent node is not used as the new parent node.

[0135] 12. Start considering the next potential parent node.

[0136] 13. Connect the potential parent node and xchild

[0137] 14. Calculate the cost of this path.

[0138] 15. Compare the cost of the new path with the cost of the original path. If the cost of the new path is smaller, perform a collision check. If the cost of the new path is larger, switch to the next potential parent node.

[0139] 16.Collision detection passed.

[0140] 17. Delete the previous edge in the tree.

[0141] 18. Add the new edge to the tree and use xpotential_parent as xparent.

[0142] 19. Traverse all potential parent nodes and get the updated tree.

[0143] After planning each inspection waypoint interval according to the above method, each track point can be written into the track file in sequence.

[0144] In line with the above, see Figure 3 , Figure 3 The present invention provides a schematic diagram of a UAV route construction device. Figure 3 As shown, the device comprises:

[0145] Acquisition unit 1, used to acquire drone inspection mission data and drone route database;

[0146] The first processing unit 2 is used to confirm the inspection sequence of the drone waypoints according to the drone inspection task data;

[0147] The second processing unit 3 is used to extract the original drone route inspection sequence from the drone route database, compare the original drone route inspection sequence with the drone waypoint inspection sequence, and obtain a drone waypoint inspection sequence comparison result;

[0148] The third processing unit 4 is used to plan the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route.

[0149] In a possible implementation, in the aspect of confirming the drone waypoint inspection sequence according to the drone inspection task data, the first processing unit is used to:

[0150] According to the drone inspection mission data, extract corresponding safety channel route data and waypoint data from the drone route database;

[0151] According to the safety channel route data and waypoint data, confirm the drone route starting entry point, n intermediate waypoints, and the drone route ending safety point;

[0152] According to the starting safety point of the human-machine route, n intermediate waypoints and the ending safety point of the drone route, the inspection sequence of the drone waypoints is confirmed.

[0153] In one possible implementation, in the aspect of confirming the inspection sequence of the drone waypoints according to the drone route starting safety point, the n intermediate waypoints and the drone route ending safety point, the first processing unit is used to:

[0154] According to the starting safety point of the UAV route, n intermediate waypoints and the ending safety point of the UAV route, the Google ortools solver is used to perform the shortest path planning to obtain the UAV waypoint inspection sequence.

[0155] In a possible implementation, in confirming the starting entry point of the drone route according to the safety channel route data and the waypoint data, the first processing unit is used to:

[0156] According to the safety channel route data and the waypoint data, sequentially calculating the waypoints and distances closest to the waypoints in the safety channel route;

[0157] Select the first waypoint corresponding to the smallest distance as the starting safety point of the drone route;

[0158] According to the starting safety point of the UAV route, confirm the second waypoint where the UAV leaves the safety channel for inspection at the beginning of the route;

[0159] According to the second waypoint, the third waypoint closest to the safety channel where the second waypoint is located is selected and confirmed as the starting entry point of the drone route.

[0160] In a possible implementation, in planning a drone route according to the comparison result of the drone waypoint inspection sequence to obtain a drone inspection route, the third processing unit is used to:

[0161] If the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part;

[0162] If the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, the improved RRT algorithm is used to plan the route that does not overlap at all or partially overlaps with the original UAV route to obtain the route as the UAV planned route for the non-overlapping part;

[0163] The planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts are spliced ​​to obtain the UAV inspection route.

[0164] In this example, the inspection order of the drone inspection task is determined based on the current drone inspection task to be executed, and the inspection order of the drone inspection task is compared with the original drone inspection route in the database. The original drone inspection route is used to plan the current drone inspection route based on the comparison results. This can reduce the amount of data processing, improve planning efficiency, and optimize the flight path.

[0165] For the above embodiments, please refer to Figure 4 , Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of the present application, as shown in the figure, includes a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, 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, and the program includes instructions for executing the following steps;

[0166] Obtain drone inspection mission data and drone route database;

[0167] According to the UAV inspection task data, confirm the UAV waypoint inspection sequence;

[0168] Extracting an original drone route inspection sequence from the drone route database, comparing the original drone route inspection sequence with the drone waypoint inspection sequence, and obtaining a drone waypoint inspection sequence comparison result;

[0169] According to the comparison result of the inspection sequence of the UAV waypoints, the UAV route is planned to obtain the UAV inspection route.

[0170] In this example, the inspection order of the drone inspection task is first determined based on the current drone inspection task to be executed, and the inspection order of the drone inspection task is compared with the original drone inspection route in the database. The original drone inspection route is used to plan the current drone inspection route based on the comparison results, which can reduce the amount of data processing, not only improve planning efficiency, but also optimize the flight path.

[0171] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that in order to realize the above functions, the terminal includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a 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. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0172] The embodiment of the present application can divide the terminal into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0173] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the drone route construction methods recorded in the above method embodiments.

[0174] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program enables a computer to execute part or all of the steps of any one of the drone route construction methods recorded in the above method embodiments.

[0175] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0176] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0177] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0178] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] In addition, the functional units in the various embodiments of the application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software program modules.

[0180] If the integrated unit is implemented 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 solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0181] 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 instructing related hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0182] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for constructing a drone route, characterized in that: include: Obtain drone inspection mission data and drone route database; According to the UAV inspection task data, confirm the UAV waypoint inspection sequence; Extracting an original drone route inspection sequence from the drone route database, comparing the original drone route inspection sequence with the drone waypoint inspection sequence, and obtaining a drone waypoint inspection sequence comparison result; According to the comparison result of the inspection sequence of the UAV waypoints, the UAV route is planned to obtain the UAV inspection route.

2. The method for constructing a UAV route according to claim 1, characterized in that: The step of confirming the inspection sequence of the drone waypoints according to the drone inspection task data and the drone route database includes: According to the drone inspection mission data, extract corresponding safety channel route data and waypoint data from the drone route database; According to the safety channel route data and waypoint data, confirm the drone route starting entry point, n intermediate waypoints, and the drone route ending safety point; According to the starting safety point of the human-machine route, n intermediate waypoints and the ending safety point of the drone route, the inspection sequence of the drone waypoints is confirmed.

3. The method for constructing a UAV route according to claim 2, characterized in that: The step of confirming the starting entry point of the drone route according to the safe channel route data and waypoint data includes: According to the safety channel route data and the waypoint data, sequentially calculating the waypoints and distances closest to the waypoints in the safety channel route; Select the first waypoint corresponding to the smallest distance as the starting safety point of the drone route; According to the starting safety point of the UAV route, confirm the second waypoint where the UAV leaves the safety channel for inspection at the beginning of the route; According to the second waypoint, the third waypoint closest to the safety channel where the second waypoint is located is selected and confirmed as the starting entry point of the drone route.

4. The method for constructing a UAV route according to claim 2, characterized in that: The method of confirming the inspection sequence of the drone waypoints according to the drone route starting safety point, n intermediate waypoints and the drone route ending safety point includes: According to the starting safety point of the UAV route, n intermediate waypoints and the ending safety point of the UAV route, the Googleortools solver is used to perform the shortest path planning to obtain the UAV waypoint inspection sequence.

5. The method for constructing a UAV route according to claim 1, characterized in that: The method of planning the route of the drone according to the comparison result of the inspection sequence of the drone waypoints to obtain the inspection route of the drone includes: If the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part; If the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, the improved RRT algorithm is used to plan the route that does not overlap at all or partially overlaps with the original UAV route to obtain the route as the UAV planned route for the non-overlapping part; The planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts are spliced ​​to obtain the UAV inspection route.

6. A drone route construction device, characterized in that: include: An acquisition unit, used to acquire UAV inspection mission data and UAV route database; A first processing unit is used to confirm the inspection sequence of the drone waypoints according to the drone inspection task data; A second processing unit is used to extract an original drone route inspection sequence from the drone route database, compare the original drone route inspection sequence with the drone waypoint inspection sequence, and obtain a drone waypoint inspection sequence comparison result; The third processing unit is used to plan the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route.

7. The drone route construction device according to claim 6, characterized in that: In the aspect of confirming the inspection sequence of the drone waypoints according to the drone inspection task data, the first processing unit is used to: According to the drone inspection mission data, extract corresponding safety channel route data and waypoint data from the drone route database; According to the safety channel route data and waypoint data, confirm the drone route starting entry point, n intermediate waypoints, and the drone route ending safety point; According to the starting safety point of the human-machine route, n intermediate waypoints and the ending safety point of the drone route, the inspection sequence of the drone waypoints is confirmed.

8. The drone route construction device according to claim 6, characterized in that: In the step of planning the drone route according to the comparison result of the drone waypoint inspection sequence to obtain the drone inspection route, the third processing unit is used to: If the comparison result of the drone waypoint inspection sequence is that the original drone route inspection sequence overlaps with the drone waypoint inspection sequence, extract the route that overlaps with the original drone route inspection sequence from the drone route database as the drone planned route of the overlapping part; If the comparison result of the UAV waypoint inspection sequence is that the original UAV route inspection sequence and the UAV waypoint inspection sequence do not overlap at all or partially overlap, the improved RRT algorithm is used to plan the route that does not overlap at all or partially overlaps with the original UAV route to obtain the route as the UAV planned route for the non-overlapping part; The planned UAV routes of the overlapping parts and the planned UAV routes of the non-overlapping parts are spliced ​​to obtain the UAV inspection route.

9. A terminal, characterized in that: The invention comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the UAV route construction method according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor executes the drone route construction method according to any one of claims 1 to 5.

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