阅读说明：本技术 一种基于同调理论的无人机覆盖搜索方法及搜索装置 (Unmanned aerial vehicle coverage search method and search device based on coherent theory ) 是由 张子用 孟伟 付敏跃 鲁仁全 于 2019-10-11 设计创作，主要内容包括：本发明涉及一种基于同调理论的无人机覆盖搜索方法及搜索装置,所述方法包括：S1：使用GPS按照设定的频率获取其位置信息,生成采样点,以及采样点的网络拓扑；S2：对网络拓扑进行降维,使获得的拓扑图具有最简形式；S3：生成一阶同调矩阵；S4：获得一阶同调阵之后,求解对应的特征值和特征向量,以获得对应空洞区域的顶点序号,确定空洞位置S5：确定空洞位置之后,将位置信息送入飞控中控制电机转动,调整无人机路径,完成对空洞区域的搜索,实现目标区域覆盖。所述装置包括无人机和无人机搭载的GPS系统、TX2开发板、飞控系统、雷达。本发明使用同调理论直接得到空洞顶点序号,确定空洞位置；可提高无人机覆盖搜索的效率。(The invention relates to an unmanned aerial vehicle coverage search method and a search device based on a coherent theory, wherein the method comprises the following steps: s1: acquiring position information of the GPS according to a set frequency by using the GPS, generating a sampling point and a network topology of the sampling point; s2: reducing the dimension of the network topology to ensure that the obtained topological graph has the simplest form; s3: generating a first-order coherence matrix; s4: after the first-order coherent matrix is obtained, solving the corresponding eigenvalue and eigenvector to obtain the vertex sequence number of the corresponding cavity region, and determining the cavity position S5: after the position of the hole is determined, the position information is sent to a flight control to control a motor to rotate, the path of the unmanned aerial vehicle is adjusted, the search of the hole area is completed, and the coverage of the target area is realized. The device includes unmanned aerial vehicle and unmanned aerial vehicle carried GPS system, TX2 development board, flight control system, radar. The method directly obtains the sequence number of the top point of the cavity by using a coherence theory and determines the position of the cavity; the efficiency of unmanned aerial vehicle coverage search can be improved.)

1. An unmanned aerial vehicle coverage search method based on a coherent theory is characterized by comprising the following steps:

s1: after the unmanned aerial vehicle takes off at an initial point, the unmanned aerial vehicle acquires position information thereof by using a GPS according to a set frequency, and generates a sampling point and a network topology of the sampling point;

s2: reducing the dimension of the network topology to ensure that the obtained topological graph has the simplest form;

s3: generating a first-order coherent matrix according to the simplest form of the topological graph;

s4: after a first-order coherent matrix is obtained, solving corresponding characteristic values and characteristic vectors to obtain vertex sequence numbers of corresponding cavity areas and determine the cavity positions;

s5: after the position of the hole is determined, the position information is sent to a flight control to control a motor to rotate, the path of the unmanned aerial vehicle is adjusted, the search of the hole area is completed, and the coverage of the target area is realized.

2. The unmanned aerial vehicle coverage search method based on the coherent theory as claimed in claim 1, wherein in the network topology of S1, when the distance between two sampling points is smaller than the search radius of the unmanned aerial vehicle, the two sampling points are connected to form a 1-simplex shape, and in the network topology, the two sampling points are connected to form a 1-simplex line;

when the distance between every two of the three sampling points is smaller than the search radius of the unmanned aerial vehicle and the detection range of the three sampling points realizes the coverage of the area surrounded by the three points, a 2-single shape is formed, and when the three sampling points are connected in pairs but not covered, 3 1-single shapes are formed;

when no points near the sampling point are connected, a 0-simplex is formed.

3. The unmanned aerial vehicle coverage search method based on coherent theory according to claim 2, wherein S2 comprises the following steps:

s2.1: obtaining a 3-simplex in the topology, namely four sampling points are connected in pairs; judging the form of the sampling point; when four 2-singlets are overlapped together, the area of the four 2-singlets is calculated, when the equation appears

when the four 2-simplex shapes are overlapped together and the area of the formed area is the sum of the areas of the three non-maximum 2-simplex shapes, only the four simplex shapes with the maximum 2-simplex shape area need to be found, and the rest redundant 2-simplex shapes are deleted;

s2.2: when the 2-simplex is covered by the surrounding 2-simplex, the simplex is deleted; and performing secondary dimensionality reduction to obtain a topological graph with a simplest form.

4. The unmanned aerial vehicle coverage search method based on coherent theory as claimed in claim 3, wherein the generation rule of the first order coherent matrix in S3 is: 1-the simplex direction is that the vertex with small serial number points to the vertex with large serial number; the 2-simplex direction is determined by two vertexes with lower sequence numbers and is generated along the 2-simplex edge, and the edge is a connecting line of the vertexes in the 2-simplex; the direction of the 1-simplex and the 2-simplex is determined for subsequent eigenvector operations.

5. The unmanned aerial vehicle coverage search method based on coherent theory as claimed in claim 4, wherein the generation formula of the first order coherent matrix in S3 is as follows:

using 1-simplex as the horizontal and vertical axes of the first-order coherent array, i, j representing the corresponding 1-simplex;

when the number of rows and the number of columns of the matrix are the same, namely i ═ j, the corresponding numerical value is r +2, when the 1-simplex corresponding to i, j forms a 2-simplex, r ═ 1, and when the 1-simplex corresponding to i, j does not form a 2-simplex, r ═ 0;

when the two 1-singles are connected and the directions of the connecting points are the same, namely the 1-singles corresponding to the connecting points are all pointed or are not pointed at the connecting points, the corresponding numerical value is 1;

when the directions are different, the corresponding numerical value is-1; when two 1-haplotypes are not connected, the number is 0.

6. The unmanned aerial vehicle coverage search method based on the coherent theory according to claim 5, wherein the eigenvectors corresponding to the 0 eigenvalue solved in S4 are weight vectors of each 1-simplex, and the 1-singletons forming the 2-singletons are added to 0 according to the determined direction weight; and the sum of 3 pairwise connected 1-simplex weights is not zero, so that the 1-simplex corresponding to the edge of the cavity can be obtained, the vertex sequence number of the corresponding cavity area can be further obtained, and the position of the cavity can be determined.

7. A searching device applying the coherent theory-based unmanned aerial vehicle coverage searching method of any one of claims 1 to 6, wherein the device comprises an unmanned aerial vehicle, a GPS system carried by the unmanned aerial vehicle, a TX2 development board, a flight control system and a radar;

the radar detects and searches for the regional obstacles and sends the detected regional obstacle information to the flight control system;

the GPS system is used for positioning and collecting the position information of the unmanned aerial vehicle and judging whether the unmanned aerial vehicle reaches the boundary; when the unmanned aerial vehicle reaches the boundary, the GPS system sends boundary information to a TX2 development board, the TX2 development board processes a network topology generated by the position sampling point of the unmanned aerial vehicle, and a coherent theory is used for solving a search hole formed by avoiding an obstacle in the search process; adjusting the path of the unmanned aerial vehicle after the position of the hole is determined; and giving a movement direction of the flight control system, sending the path information and the movement direction information to the flight control system, and controlling the flight path of the unmanned aerial vehicle by the flight control system according to the regional obstacle information detected by the radar, the position information of the unmanned aerial vehicle sent by the GPS system, the path information and the movement direction information sent by the TX2 development board to complete hole searching so as to realize coverage control.

Technical Field

The invention relates to the field of unmanned aerial vehicle searching, in particular to an unmanned aerial vehicle coverage searching method and device based on a coherent theory.

Background

The starting is earlier in the aspect of using the unmanned aerial vehicle to search the region abroad, and good effects are obtained through long-term application and research. At present, the regional search range of foreign unmanned aerial vehicles mainly comprises forest fires, earthquakes, typhoons, volcanoes and the like. In recent years, the disaster management department in China also increases the application and research strength of unmanned aerial vehicle disaster monitoring, and achieves certain achievements. The unmanned aerial vehicle is mainly applied in the civil field in the aspects of aerial photography, aerial surveying and mapping, traffic monitoring, fire fighting, artificial precipitation and the like. The application of unmanned aerial vehicle in the farmland begins to appear gradually, mainly concentrates on fields such as farmland information remote sensing, calamity early warning, fertilization medicine spraying.

In the unmanned aerial vehicle application process, firstly, area mapping needs to be carried out on an area to be searched. The coverage search of a search area needs to be realized in the image building process, and the unmanned aerial vehicle can be blocked by an obstacle in the search process and constrained by the minimum turning radius of the unmanned aerial vehicle, so that a search hole can be generated in the obstacle avoiding process. How the unmanned aerial vehicle realizes the search of the holes appearing in the covering process becomes the main problem of the current unmanned aerial vehicle search.

When the unmanned aerial vehicle carries out coverage search on an unknown area, the unmanned aerial vehicle generates a cavity in the process of avoiding the obstacle due to the obstacle blocking and the minimum turning radius constraint of the unmanned aerial vehicle. The traditional method needs to record all waypoint information and find a search hole by comparing the waypoint information with a global map, and the traditional method needs an unmanned aerial vehicle to have a larger storage space and a higher processing speed. And the storage space and the processing speed of the existing unmanned aerial vehicle cause that the unmanned aerial vehicle coverage searching efficiency is low.

Disclosure of Invention

The invention provides an unmanned aerial vehicle coverage search method and a search device based on a coherent theory, aiming at overcoming the defect of low unmanned aerial vehicle coverage search efficiency in the prior art.

The searching method comprises the following steps:

s1: after the unmanned aerial vehicle takes off at an initial point, the unmanned aerial vehicle acquires position information thereof by using a GPS according to a set frequency, and generates a sampling point and a network topology of the sampling point;

in the network topology, when the distance between two sampling points is smaller than the search radius of the unmanned aerial vehicle, the two sampling points are connected to form a 1-simplex shape (the two sampling points are connected to form a 1-single line in the network topology), and the two sampling points are connected to form a 1-single line in the network topology;

when the distance between every two of the three sampling points is smaller than the search radius of the unmanned aerial vehicle and the detection range of the three sampling points realizes the coverage of the area surrounded by the three points, a 2-single shape is formed, and when the three sampling points are connected in pairs but not covered, 3 1-single shapes are formed;

when no point is connected near the sampling point, a 0-simplex shape is formed;

the search radius of the unmanned aerial vehicle is r, and when the distance between two sampling points (namely the network topology top points) is smaller than r, the two points are connected to form a 1-simplex. When the distance between every two of the three sampling points is smaller than r and the detection range of the three sampling points realizes the coverage of the area surrounded by the three points, a 2-single shape is formed, and when every two of the three sampling points are connected but not covered, 3 1-single shapes are formed. And so on, when the n sampling points are connected two by two and form coverage, the n-simplex is called. When no points near the sampling point are connected, a 0-simplex is formed.

S2: when 3-simplex exists in the network topology, reducing the dimension of the network topology to ensure that the obtained topological graph has the simplest form;

s3: generating a first-order coherent matrix according to the simplest form of the topological graph;

s4: after the first-order coherent matrix is obtained, solving the corresponding characteristic value and the characteristic vector to obtain the vertex sequence number of the corresponding cavity area and determine the cavity position

S5: after the position of the hole is determined, the position information is sent to a flight control to control a motor to rotate, the path of the unmanned aerial vehicle is adjusted, the search of the hole area is completed, and the coverage of the target area is realized.

The invention provides an unmanned aerial vehicle coverage searching method based on a coherent theory. When the unmanned aerial vehicle carries out coverage search on an unknown area, the unmanned aerial vehicle generates a cavity in the process of avoiding the obstacle due to the obstacle blocking and the minimum turning radius constraint of the unmanned aerial vehicle. The traditional method needs to record all waypoint information and find out a search hole through comparison with a global map, and the method needs an unmanned aerial vehicle to have a large storage space and a high processing speed. The invention realizes unmanned aerial vehicle coverage search under the condition that the unmanned aerial vehicle does not have larger storage space and higher processor processing speed.

Preferably, S2 includes the steps of:

s2.1: obtaining a 3-simplex in the topology, namely four sampling points are connected in pairs; judging the form of the sampling point; when four 2-singlets are overlapped together, the area of the four 2-singlets is calculated, when the equation appears Then, a redundant matrix is obtained, and any pair of redundant matrices is deleted;

when the four 2-simplex shapes are overlapped together and the area of the formed area is the sum of the areas of the three non-maximum 2-simplex shapes, only the four simplex shapes with the maximum 2-simplex shape area need to be found, and the rest redundant 2-simplex shapes are deleted;

s2.2: when the 2-simplex is covered by the surrounding 2-simplex, the simplex is deleted; and performing secondary dimensionality reduction to obtain a topological graph with a simplest form.

Preferably, the generation rule of the first-order coherence matrix in S3 is: 1-the simplex direction is that the vertex with small serial number points to the vertex with large serial number; the 2-simplex direction is determined by two vertexes with lower sequence numbers and is generated along the 2-simplex edge (the edge is the connecting line of the vertexes in the 2-simplex), and the edge is the connecting line of the vertexes in the 2-simplex; the direction of the 1-simplex and the 2-simplex is determined for subsequent eigenvector operations.

Preferably, the generation formula of the first-order coherence matrix in S3 is as follows:

using 1-simplex as the horizontal and vertical axes of the first-order coherent array, i, j representing the corresponding 1-simplex;

when the number of rows and the number of columns of the matrix are the same (i ═ j), the corresponding numerical value is r +2, when the 1-simplex corresponding to i, j forms a 2-simplex, r ═ 1, and when the 1-simplex corresponding to i, j does not form a 2-simplex, r ═ 0;

when the two 1-singles are connected and the directions of the connecting points are the same, namely the 1-singles corresponding to the connecting points are all pointed or are not pointed at the connecting points, the corresponding numerical value is 1;

when the directions are different, the corresponding value is-1. When two 1-haplotypes are not connected, the number is 0.

Preferably, the eigenvector corresponding to the 0 eigenvalue solved in S4 is the weight vector of each 1-simplex, and the 1-singletons forming the 2-singletons are added to 0 according to the determined direction weight; and the sum of 3 pairwise connected 1-simplex weights is not zero, so that the 1-simplex corresponding to the edge of the cavity can be obtained, the vertex sequence number of the corresponding cavity area can be further obtained, and the position of the cavity can be determined.

The invention also provides a searching device applying the unmanned aerial vehicle coverage searching method based on the coherent theory, wherein the device comprises an unmanned aerial vehicle, a GPS system carried by the unmanned aerial vehicle, a TX2 development board, a flight control system and a radar; the TX2 development board is a JETSON TX2 development board.

The radar detects and searches for the regional obstacles and sends the detected regional obstacle information to the flight control system;

the GPS system is used for positioning and collecting the position information of the unmanned aerial vehicle and judging whether the unmanned aerial vehicle reaches the boundary; when the unmanned aerial vehicle reaches the boundary, the GPS system sends boundary information to a TX2 development board, the TX2 development board processes a network topology generated by the position sampling point of the unmanned aerial vehicle, and a coherent theory is used for solving a search hole formed by avoiding an obstacle in the search process; adjusting the path of the unmanned aerial vehicle after the position of the hole is determined; and giving a movement direction of the flight control system, sending the path information and the movement direction information to the flight control system, and controlling the flight path of the unmanned aerial vehicle by the flight control system according to the regional obstacle information detected by the radar, the position information of the unmanned aerial vehicle sent by the GPS system, the path information and the movement direction information sent by the TX2 development board to complete hole searching so as to realize coverage control.

The hardware system of the searching device comprises a flight control system, a GPS (global positioning system), a laser radar and a JETSONTX2 development board. The unmanned aerial vehicle uses GPS positioning to generate sampling point position information and judges whether the unmanned aerial vehicle reaches a boundary. Search area obstacles are detected using lidar.

The method comprises the steps that a JETSON TX2 development board is used for recording position information of waypoints and simultaneously generating topological relations among the waypoints, when the unmanned aerial vehicle moves to a boundary area from a starting point, a second-order coherence matrix is generated by network topology generated by the waypoints according to vertex sequence numbers, and sequence numbers of vertices of generated topological cavities are obtained by solving eigenvectors of the matrix. And during operation, the sequence number of the top point of the topological cavity can be obtained only by depending on the topological relation of the sampling points without traversing the position information of all the sampling points. Therefore, the position of the cavity generated in the searching process is obtained, the path of the unmanned aerial vehicle is planned according to the position, and coverage searching of the area to be searched is achieved.

Compared with the prior art, the technical scheme of the invention has the beneficial effects that: the invention can improve the efficiency of coverage search of the unmanned aerial vehicle; the invention uses the coherence theory to directly obtain the serial number of the vertex of the cavity and determine the position of the cavity. In the process of acquiring the position of the cavity, the invention only needs to process the network topology formed among the sampling points, does not need to traverse the position information of each sampling point, and improves the operation speed.

Drawings

Fig. 1 is a flowchart of an unmanned aerial vehicle coverage search method based on the coherence theory in embodiment 1.

Fig. 2 is a schematic view in simplex form.

Fig. 3 is a trajectory diagram of the drone.

Fig. 4 is a network topology diagram of the trajectory of the drone.

FIG. 5 is a schematic view of a 4-simplex configuration.

Fig. 6 is a topology diagram of the unmanned aerial vehicle trajectory network after the initial dimensionality reduction.

Fig. 7 is a network topology diagram of the unmanned aerial vehicle trajectory after two dimensionalities reduction.

FIG. 8 is a schematic view of the 2-simplex orientation.

Fig. 9 is a schematic diagram of the coverage search device of the unmanned aerial vehicle based on the coherence theory in embodiment 2.

Detailed Description

The drawings are for illustrative purposes only and are not to be construed as limiting the patent;

for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;

it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.

The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.