A multi-target UAV patrol path planning method

Abstract

The present invention relates to the field of computer graphics and geographic information science and technology, and specifically discloses a method for planning a patrol path for a drone with multiple target points. The present invention adopts the mutual constraints of lines and surfaces in two-dimensional space, and is guided by the idea of ​​dimensionality increase and dimensionality reduction. The present invention uses the deep mining of the necessary conditions for the node degree of the free Hamiltonian path to be 2, and through the deletion and retention states of the point-adjacent triangle, the goal of solving the patrol path of the drone is achieved by reducing the node degree to 2.

Description

Technical Field

[0001] The invention relates to the fields of computer science and geographic information science, and in particular to a method for planning a patrol path of an unmanned aerial vehicle with multiple target points. Background Art

[0002] The multi-target UAV patrol path planning is a core content of the UAV mission planning system and is widely used in logistics, transportation, urban planning, emergency response and other fields. The problem is solved by particle swarm optimization, multi-target genetic algorithm, etc., and cluster thinking is often used. By simulating biological foraging and other behaviors to analyze multi-target problems, it can be attributed to the biological thinking derivative algorithm. Current scholars rely on this thinking, integrate other relevant influencing factors or perform operator optimization to achieve the search goal of multi-target UAV patrol paths. The advantage of this type of algorithm is high efficiency but poor accuracy. According to the basic thinking of graphics, the optimal multi-target UAV patrol path must meet the basic requirements of graphics, such as no line intersection, etc. Based on this, more shortest path constraints can be discovered in the multi-target UAV patrol path search to achieve a fast and accurate solution to the problem.

[0003] Academically, the search for drone patrol paths with multiple target points belongs to the category of free Hamiltonian paths. Hamiltonian paths are paths that reach all nodes, and their optimal solution is TSP, which is also a classic NP-type problem: the traveler problem. In the past hundred years, scholars have failed to perfectly solve the Hamiltonian path problem and the TSP path problem from a theoretical and technical perspective, so that the problem has become one of the classic problems in the fields of logistics, tourism, and microelectronics design. The difficulty of the Hamiltonian path problem is mainly reflected in the diversity and uncertainty of path selection. Traditional scientific thinking believes that this problem is a permutation and combination in the field of mathematics, and its complexity is related to N! Therefore, its solution is also studied from the fields of mathematics, logic, and traditional computer graphics.

[0004] The Hamiltonian path problem and the TSP path problem still belong to the field of natural sciences and are the concretization of space science problems. Therefore, the principle of "the more constraints there are, the more likely the problem is to be solved" in natural sciences must also be applied. Combined with the law of solving natural science problems: In solving natural science problems, necessary conditions are often easier to discover than necessary and sufficient conditions. Based on this, the solution to the problem cannot be considered only from traditional scientific fields such as logical thinking and mathematics. It is necessary to combine practical problems to find more necessary conditions to solve the problem.

[0005] 80% of the problems in human society are related to spatial location. Spatial information is reflected in points, lines and surfaces in computer graphics. Therefore, it can be considered that most human problems are related to points, lines and surfaces: spatial problems are not only affected by logical thinking, but also constrained by spatial relationships. It can be said that spatial topological relationships, which are special constraints that do not depend on image size, shape, position, and direction, are more extensive and common implicit problem constraints. When facing human spatial problems, it is even more necessary to look at the essence of the problem with spatial thinking of points, lines and surfaces, and then explore the root of the problem in order to find the key to solving the problem.

[0006] The Hamiltonian path is a typical NP problem. Its essence is to traverse all nodes, and each node is only passed once, that is, one in and one out. It is reflected in the nodes as line segments connecting in and out. This is called degree in academia, that is, the number of lines connecting nodes. A closed line with a degree of two is a Hamiltonian cycle, which is reflected in computer graphics as a single simple closed polygon. Based on this, it can be understood that the Hamiltonian cycle is essentially a point connection problem, but it is reflected in space as a closed surface. At this point, the Hamiltonian path problem integrates points, lines and surfaces in topological relationships. The Hamiltonian path is a line connection problem, but it involves two-dimensional space, that is, lines and polygons are intertwined, which is a line problem. The two-dimensionalization of a one-dimensional problem, the expansion of a one-dimensional line to a two-dimensional surface space, and the infinite dimensionality of the solution space are the fundamental reasons why the problem shows exponential growth and is difficult to solve quickly.

[0007] The patrol path planning of UAV with multiple target points is a core content of the UAV mission planning system. The solution of this problem often adopts cluster thinking such as particle swarm algorithm and multi-objective genetic algorithm. By simulating the behavior analysis of biological foraging and other multi-objective problems, it can be attributed to biological thinking algorithms. Most scholars' research relies on this thinking, integrates other relevant influencing factors or performs operator optimization to achieve the goal of unconstrained patrol path planning of UAV with multiple target points. However, the planning efficiency of the above algorithm is low during planning. From the basic thinking of graphics, it can be seen that the unconstrained patrol path of UAV with multiple target points meets the basic requirements of graphics. When planning, all target points need to be connected, and each target point can only be connected once, so as to ensure that the same target point will not be patrolled twice during patrol. This is the same as the above Hamiltonian path problem, but the difficulty of the above patrol path will still increase exponentially with the number of targets when planning. Therefore, it is of great significance to provide a simple and efficient planning method for UAV patrol paths with multiple target points. Summary of the invention

[0008] The present invention aims to solve at least one of the above-mentioned technical problems and provide a method for planning a patrol path of a multi-target UAV, which can improve the planning efficiency of the patrol path of the UAV.

[0009] In order to achieve the above object, the technical solution adopted by the present invention is: a method for planning a patrol path of a multi-target UAV, comprising the following steps:

[0010] S1, obtain the patrol point coordinates and distribute the patrol points in a two-dimensional plane;

[0011] S2, construct a triangulated network through patrol points, so that all patrol points are distributed in the triangulated network, and convert the triangulated network into a surface;

[0012] S3, searching any patrol point in the triangulated network as the initial surround point, taking the initial surround point as the center, searching for a triangle containing the initial surround point as a selected triangle, and the selected triangles constitute a selected area, and selecting any selected triangle in the selected area as a triangle to be deleted;

[0013] S4, searching for another patrol point outside the selected area as a surrounding point, determining the selected area with the surrounding point as the center, selecting any selected triangle in the selected area as a triangle to be deleted, and the selected triangles to be deleted do not have adjacent edges or points;

[0014] S5, repeat step 4 until the search for the triangle to be deleted in the entire triangulated network is completed;

[0015] S6, searching for patrol points on the outermost edge line in the triangulated network, and treating patrol points not on the to-be-deleted triangle as isolated points. If there are no isolated points, proceeding to the next step. If there are isolated points, searching for a triangle including the isolated points as a merged triangle. If the merged triangle is adjacent to the edge of the to-be-deleted triangle, and there is no situation where the adjacent triangles are only through points, then stopping the search and proceeding to the next step. Otherwise, searching for another triangle adjacent to the edge of the merged triangle as a new merged triangle, and then searching based on the new merged triangle, repeating the above search method, and if there is no situation where the adjacent triangles are only through points, then stopping the search and proceeding to the next step.

[0016] S7, deleting the triangle to be deleted and the merged triangle;

[0017] S8, searching whether there is an island hole in the triangulated network, if there is no island hole, proceeding to the next step, if there is an island hole, removing the island hole;

[0018] S9. Merge the remaining triangles in the triangulated network, and the polygonal boundary obtained after the merging is the planning result of the path.

[0019] Preferably, the path planning method is used for planar path planning.

[0020] Preferably, the triangulated network in step S2 is preferably a Delaunay triangulated network.

[0021] Preferably, it is characterized in that, in the step S9, a side line shared by adjacent triangles is deleted to achieve merging of the triangles.

[0022] Preferably, in step S3, any patrol point except the outermost edge line in the triangulated network is searched as the initial surround point.

[0023] Preferably, in step S8, when removing island holes, the triangles adjacent to the edges of the island holes are searched. If the triangle includes the outermost edge line of the triangulated network, the triangle is merged with the island hole to remove the island hole. If the triangle does not include the outermost edge line of the triangulated network, the triangle is merged with the island hole and used as a new island hole to search for triangles of adjacent edges. The above steps are repeated until the merged triangle includes the outermost edge line of the triangulated network. If a hanging point appears after the searched triangle is merged with the island hole, the triangle cannot be used as a search result.

[0024] Beneficial effects are: compared with the prior art, the multi-target UAV patrol path planning method of the present invention has the following beneficial effects:

[0025] 1. The multi-target path problem of UAVs is a point connection problem, but expanding it to the surface area and setting reasonable constraints, that is, achieving the solution through adjacent edges, is a specific practice of exploring problem constraints in natural sciences to accelerate problem solving.

[0026] 2. The present invention achieves the goal of removing hanging points by filtering out all hanging points and then deleting adjacent triangles. Its purpose is to reduce the connectivity of nodes, thereby achieving the goal of reducing the node dimension by 2 without the occurrence of hanging points, completing the integration of simple polygons, and simplifying and concretizing the constraints.

[0027] 3. The invention relies on the different judgments of the states to be deleted in the adjacent triangles of the point, and is completed through the logical operation of spatial query, that is, the logical processing of multi-dimensional spatial problems, which is the one-dimensional operation of two-dimensional problems and the concrete manifestation of dimensionality reduction operation, achieving the simplification and rapid solution of problems. It is a new and efficient mathematical algorithm different from biological algorithms.

[0028] 4. The invention connects logistics points through Delaunay triangulation, which is essentially a preferred triangle with the advantage of a larger area under the same perimeter. In other words, when the sample space area is given, the triangle has the advantage of a shorter perimeter, thereby achieving overall optimization of the path length when the path is contracted, and the result is closer to the optimal solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0030] Figure 1It is a schematic diagram near the suspension point 1;

[0031] Figure 2 It is a schematic diagram near the second hanging point;

[0032] Figure 3 It is a schematic diagram for reducing the suspension point degree to 2;

[0033] Figure 4 A schematic diagram of merging triangulated networks to obtain a single polygon whose boundary contains all nodes;

[0034] Figure 5 This is a schematic diagram of the distribution of patrol points;

[0035] Figure 6 Schematic diagram for constructing a triangulated network;

[0036] Figure 7 It is a schematic diagram of triangulated surface;

[0037] Figure 8 Schematic diagram of the selected initial surround point and the selected area;

[0038] Fig. 9 This is a schematic diagram for selecting the first triangle to be deleted;

[0039] Fig.10 This is a schematic diagram for selecting the second triangle to be deleted;

[0040] Fig.11 It is a schematic diagram of selecting all triangles to be deleted through the selected area;

[0041] Fig.12 A schematic diagram for searching for merged triangles;

[0042] Fig.13 for Fig.12 Schematic diagram of isolated points in the figure;

[0043] Fig.14 A schematic diagram of merging triangles through isolated point search;

[0044] Fig.15 A schematic diagram of deleting triangles to be deleted and merging triangles;

[0045] Fig.16 Schematic diagram for removing island holes;

[0046] Fig.17 This is a schematic diagram after merging the remaining triangles;

[0047] Fig.18 This is a schematic diagram of the path planning results;

[0048] Fig.19 is a schematic diagram of two adjacent triangles;

[0049] Fig. 20 Schematic diagram of merging two adjacent triangles. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] It should be noted that when a component is referred to as being "fixed to" another component, it may be directly on the other component or there may be a central component. When a component is considered to be "connected to" another component, it may be directly connected to the other component or there may be a central component at the same time. When a component is considered to be "set on" another component, it may be directly set on the other component or there may be a central component at the same time. When a component is referred to as being "set in the middle", it does not only mean being set in the middle, as long as it is not set at both ends within the range defined by the middle. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0053] like Figures 1 to 4 As shown, the essence of the path problem is the route selection to reach the target point. It is a one-dimensional line problem in multi-dimensional space. Its ultimate goal is to select a line, and the selection is logical. The line is the connection relationship between points and the boundary of polygons in two-dimensional space. Distributed in multi-dimensional space, the path problem involves the basic graphics elements of points, lines and surfaces from zero dimension to two dimension.

[0054] From the basic thinking of solving problems in natural sciences, we can know that the discovery of necessary conditions in problem solving is often easy to discover necessary and sufficient conditions. Based on this, based on logical thinking, we can make the following analysis: From the basic concept of graphics, if an adjacent edge has only two nodes, if the adjacent edge is removed, it is manifested in the graphics operation as the merging of the adjacent edge graphics, and there will be no hanging points at both ends. In other words, the processing of adjacent edges will only reduce the node degree, and there will be no hanging point problem. Based on this analysis, if the above strips are connected through this thinking, the replacement polygons that meet the requirements will eventually be normalized into a simple polygon again, and its boundary is the desired Hamiltonian path solution. It should be noted that two triangles are adjacent through edges, which is defined as the edges of the two triangles being adjacent, and two triangles are adjacent only through vertices, which is defined as the points of the two triangles being adjacent.

[0055] Based on this, the present application discloses a multi-target UAV patrol path planning method, which includes the following steps:

[0056] S1, obtain the patrol point coordinates and distribute the patrol points in a two-dimensional plane;

[0057] S2, construct a triangulated network through patrol points, so that all patrol points are distributed in the triangulated network, and convert the triangulated network into a surface;

[0058] S3, searching any patrol point in the triangulated network as the initial surround point, taking the initial surround point as the center, searching for a triangle containing the initial surround point as a selected triangle, and the selected triangles constitute a selected area, and selecting any selected triangle in the selected area as a triangle to be deleted;

[0059] S4. Search for another patrol point outside the selected area as a surrounding point, determine the selected area with the surrounding point as the center, select any selected triangle in the selected area as the triangle to be deleted, and there is no situation where the edges and points are adjacent between the selected triangles to be deleted; preferably, any patrol point except the outermost edge line in the triangulated network can be searched as the initial surrounding point.

[0060] S5, repeat step 4 until the search for the triangle to be deleted in the entire triangulated network is completed;

[0061] S6, searching for patrol points on the outermost edge line in the triangulated network, and treating patrol points that are not on the triangle to be deleted as isolated points. If there are no isolated points, proceed to the next step. If there are isolated points, search for a triangle including the isolated point as a merged triangle. If the merged triangle is adjacent to the edge of the triangle to be deleted, and there is no situation where they are adjacent only through points, stop searching and proceed to the next step. Otherwise, search for another triangle adjacent to the edge of the merged triangle as a new merged triangle. Repeat the above search method until the merged triangle found is adjacent to the edge of the triangle to be deleted, and there is no situation where they are adjacent only through points. Then stop searching and proceed to the next step.

[0062] S7, deleting the triangle to be deleted and the merged triangle;

[0063] S8, searching whether there is an island hole in the triangulated network, if there is no island hole, proceeding to the next step, if there is an island hole, removing the island hole;

[0064] S9. Merge the remaining triangles in the triangulated network, and the polygonal boundary obtained after the merging is the planning result of the path.

[0065] The specific planning steps of the path are as follows:

[0066] S1. Obtain the patrol point coordinates and distribute the patrol points in a two-dimensional plane, such as Figure 5 As shown;

[0067] S2. Construct a triangulated network through patrol points so that all patrol points are distributed in the triangulated network, such as Figure 6 As shown, the triangulated network is converted into a surface through topological faceting, as shown Figure 7 As shown;

[0068] S3, search any patrol point in the triangulation network as the initial surround point, take the initial surround point as the center, search for the triangle containing the initial surround point as the selected triangle, and the selected triangles constitute a selected area, such as Figure 8 As shown in the figure, select any selected triangle in the selected area as the triangle to be deleted, such as Fig. 9 As shown;

[0069] S4, search for another patrol point outside the selected area as a surrounding point, determine the selected area with the surrounding point as the center, select any selected triangle in the selected area as a triangle to be deleted, and there is no edge adjacent and point adjacent situation between the selected triangles to be deleted, such as Fig.10 As shown;

[0070] S5, repeat step 4 until the search for the triangle to be deleted in the entire triangulated network is completed, such as Fig.11 As shown;

[0071] S6, search the patrol points on the outermost edge of the triangulated network, and take the patrol points that are not on the triangle to be deleted as isolated points. If there are no isolated points, go to the next step, such as Fig.12 As shown in , if there is an isolated point, search for a triangle including the isolated point as a merged triangle. If the merged triangle is adjacent to the edge of the triangle to be deleted and there is no situation where they are adjacent only through points, stop searching and proceed to the next step. Otherwise, Fig.13 As shown, the merged triangle is not adjacent to the edge of the triangle to be deleted, then Fig.14The method shown searches for another triangle adjacent to the edge of the merged triangle as a new merged triangle, and repeats the above search method until the searched merged triangle is adjacent to the edge of the triangle to be deleted, and there is no situation where they are adjacent only through points, so that all isolated points in the triangulated network are removed, and the search for merged triangles is stopped, and the next step is entered. It should be noted that in the search for merged triangles, if there is a merged triangle that completely surrounds a patrol point, or the merged triangle and the triangle to be deleted completely surround a patrol point, then the last merged triangle searched cannot be used as the search result. The selected area above completely surrounds a patrol point in the middle. Therefore, in order to avoid this phenomenon, it is necessary to select a triangle as the triangle to be deleted for deletion to avoid the patrol point being completely surrounded.

[0072] S7, deleting the triangle to be deleted and the merged triangle, such as Fig.15 As shown;

[0073] S8, search whether there is an island hole in the triangulation network, if there is no island hole, go to the next step, if there is an island hole, remove the island hole, such as Fig.16 As shown;

[0074] S9, such as Fig.17 and 18 As shown, the remaining triangles in the triangulated network are merged, and the polygonal boundary obtained after the merger is the planning result of the path.

[0075] Preferably, in step S9, a side line shared by adjacent triangles is deleted to merge the triangles, such as Fig.19 As shown in , two triangles are adjacent and share a side line. After deleting the shared side line, the two triangles are merged, and there will be no hanging points after the merger, as shown in Fig. 20 As shown, the polygon obtained after merging is then merged with the remaining triangles by the above method of deleting the shared edges, thereby completing the merging of all triangles.

[0076] In this embodiment, after deleting the triangles to be deleted and merging the triangles, a hole will be formed in the triangulated network. If the hole is not on the outermost edge of the triangulated network, an island hole will be formed in the triangulated network. The island hole needs to be removed during path planning. For step S, when removing the island hole, the triangle adjacent to the edge of the island hole can be searched. If the triangle includes the outermost edge of the triangulated network, the triangle is merged with the island hole to remove the island hole. If the triangle does not include the outermost edge of the triangulated network, the triangle is merged with the island hole as a new island hole to search for triangles with adjacent edges. The above steps are repeated until the merged triangle includes the outermost edge of the triangulated network. If a hanging point appears after the searched triangle is merged with the island hole, the triangle cannot be used as a search result. If the new island hole is adjacent to other island holes, a triangle adjacent to the edges of the two island holes is searched as a connected triangle, and the connected triangle is deleted to connect the two island holes.

[0077] It should be noted that the path planning method of the present application can not only be automatically planned by a computer, but also can be manually planned by plane drawing.

[0078] The above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Any modification or equivalent substitution that does not depart from the spirit and scope of the present invention shall be included in the scope of the technical solution of the present invention.

Claims

1. A multi-target UAV patrol path planning method, characterized in that: The following steps are involved: S1, obtain the patrol point coordinates and distribute the patrol points in a two-dimensional plane; S2, construct a triangulated network through patrol points, so that all patrol points are distributed in the triangulated network, and convert the triangulated network into a surface; S3, searching any patrol point in the triangulated network as the initial surround point, taking the initial surround point as the center, searching for a triangle containing the initial surround point as a selected triangle, and the selected triangles constitute a selected area, and selecting any selected triangle in the selected area as a triangle to be deleted; S4, searching for another patrol point outside the selected area as a surrounding point, determining the selected area with the surrounding point as the center, selecting any selected triangle in the selected area as a triangle to be deleted, and the selected triangles to be deleted do not have adjacent edges or points; S5, repeat step 4 until the search for the triangle to be deleted in the entire triangulated network is completed; S6, searching for patrol points on the outermost edge line in the triangulated network, and treating patrol points that are not on the triangle to be deleted as isolated points. If there are no isolated points, proceed to the next step. If there are isolated points, search for a triangle including the isolated point as a merged triangle. If the merged triangle is adjacent to the edge of the triangle to be deleted, and there is no situation where they are adjacent only through points, stop searching and proceed to the next step. Otherwise, search for another triangle adjacent to the edge of the merged triangle as a new merged triangle. Repeat the above search method until the merged triangle found is adjacent to the edge of the triangle to be deleted, and there is no situation where they are adjacent only through points. Then stop searching and proceed to the next step. S7, deleting the triangle to be deleted and the merged triangle; S8, search whether there is an island hole in the triangulated network. If there is no island hole, proceed to the next step. If there is an island hole, remove the island hole. When removing the island hole, search for triangles adjacent to the island hole. If the triangle includes the outermost edge line of the triangulated network, merge the triangle with the island hole and remove the island hole. If the triangle does not include the outermost edge line of the triangulated network, merge the triangle with the island hole as a new island hole to search for triangles with adjacent edges. Repeat the above steps until the merged triangle includes the outermost edge line of the triangulated network. If a hanging point appears after the searched triangle is merged with the island hole, the triangle cannot be used as a search result. S9. Merge the remaining triangles in the triangulated network, and the polygonal boundary obtained after the merger is the planning result of the path.

2. The method for planning a multi-target UAV patrol path according to claim 1, characterized in that: The path planning method is used for planar path planning.

3. The method for planning a multi-target UAV patrol path according to claim 1, characterized in that: The triangulated network in step S2 is a Delaunay triangulated network.

4. The method for planning a multi-target UAV patrol path according to claim 1, characterized in that: In step S9, a side line shared by adjacent triangles is deleted to merge the triangles.

5. The method for planning a multi-target UAV patrol path according to claim 1, characterized in that: In step S3, any patrol point except the outermost edge line in the triangulated network is searched as the initial surround point.

Images