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Unmanned system rapid relocation method based on environmental geometry and topological characteristics

A technology of topological features and geometric features, which is applied in the field of rapid relocation of unmanned systems based on environmental geometry and topological features, can solve the problem that the convergence speed of the particle filter algorithm is difficult to guarantee, and achieve the effect of improving the convergence speed

Active Publication Date: 2020-11-27
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problem that the convergence speed of the existing particle filter algorithm in the above-mentioned prior art is difficult to guarantee, the present invention provides a fast relocation method for unmanned systems based on environmental geometry and topological features, and solves the problem of fast relocation of unmanned systems. Good convergence speed and guaranteed accuracy

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  • Unmanned system rapid relocation method based on environmental geometry and topological characteristics
  • Unmanned system rapid relocation method based on environmental geometry and topological characteristics
  • Unmanned system rapid relocation method based on environmental geometry and topological characteristics

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Embodiment 1

[0066] Such as figure 1 Shown is an embodiment of a fast relocation method for an unmanned system based on environmental geometric and topological features, including the following steps:

[0067] Step 1: Use the laser SLAM algorithm to obtain the grid map and convert it into a simplified map to extract the geometric features in the environment. The geometric features include the endpoints and corners of obstacles in the environment as map nodes, and the distance between nodes as adjacency matrix;

[0068] The method of transforming into a simplified map is as follows: the grid of the grid map has three states: "occupied", "free" and "unknown", and the pixel values ​​​​are represented by 0, 255, and 205, which respectively represent obstacles in the grid , no obstacle and unknown state; the simplified map is a collection of obstacle edges, and the "occupied" grid whose adjacent grid is "free" is extracted as the simplified map.

[0069] The steps of map node extraction are: ...

Embodiment 2

[0104] Another embodiment of the unmanned system fast relocation method based on environmental geometry and topological features is different from Embodiment 1 in that the number of selected key points is two, and the rough positioning method is as follows: Figure 4 As shown, the straight-line distances between the unmanned system and the key points are the radii r1 and r2 respectively, such as Figure 5 As shown, the matching node combination in P is used as the center of the circle, two circles are constructed with r1 and r2 as the radius, and the intersection points C and D of the two circles are used as rough positioning points.

[0105] The specific expression of the intersection point of two circles is:

[0106]

[0107]

[0108] in,

[0109] In the formula, the matching node in P is the center of the circle, and the coordinates are known as (x 1 ,y 1 ), (x 2 ,y 2 ); the connection line of the intersection point and the connection line of the matching node in...

Embodiment 3

[0111] Another embodiment of the method for rapid relocation of unmanned systems based on the geometric and topological features of the environment is implemented in an environment where linear features are the main features.

[0112] Step 1: Use the Turtlebot robot with the RPlidarA3 laser for laser SLAM mapping, and provide the original grid map and laser data for testing for this method.

[0113] The method of converting a grid map into a simplified map is as follows: the grid of the grid map has three states: "occupied", "free" and "unknown", and the pixel values ​​​​are represented by 0, 255, and 205, respectively representing the status of the grid. The grid has obstacles, no obstacles and unknown status; the simplified map is a collection of obstacle edges, and the "occupied" grid whose adjacent grid is "free" is extracted as the simplified map, and the result is as follows Figure 6 shown.

[0114] The steps of map node extraction are:

[0115] S1.1: Carry out curve ...

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Abstract

The invention relates to an unmanned system rapid relocation method based on environmental geometrical and topological characteristics. The method comprises the following steps: extracting geometricalcharacteristics in the environment by using a grid map obtained by a laser SLAM algorithm, including taking end points and corner points of obstacles in the environment as map nodes and taking distances among the nodes as an adjacent matrix; establishing an environment geometrical characteristic topological map; extracting key points and geometrical information of an obstacle in current laser data, carrying out data association matching in cooperation with an environment geometrical characteristic topological map to obtainmap nodes corresponding to the key points; and carrying out coarse positioning of the unmanned system through cooperation of geometrical information and a node matching result, and finally, locating the coarse positioning result accurately. Compared with a positioning method that particles are randomly generated in a global range through particle filtering and then laser data matching scores are used as guidance, the method has the advantages that the search area isdetermined in a more targeted and more efficient mode, and meanwhile the situation that the search area falls into a local optimal value can be avoided.

Description

technical field [0001] The present invention relates to the field of positioning of unmanned systems, and more specifically, to a fast relocation method for unmanned systems based on environmental geometric and topological features. Background technique [0002] The accurate positioning of the unmanned system is the prerequisite for the unmanned system to navigate autonomously and perform tasks, but there are three situations that will affect the positioning effect. First of all, unmanned vehicles and robots may encounter the "kidnapping problem" during the positioning process, that is, they are passively displaced to any position on the map, but the system thinks that they stay in place and the positioning error occurs. Secondly, during the operation of the unmanned system, due to sudden sensor failures, such as the loss of odometer data, the pose cannot be updated, resulting in the failure of positioning. Finally, due to the characteristics of the current SLAM algorithm, ...

Claims

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Application Information

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IPC IPC(8): G01C21/00G01C21/20
CPCG01C21/005G01C21/20
Inventor 熊会元杜继能梁凡钱沛聪
Owner SUN YAT SEN UNIV