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Path planning method of improved A* algorithm based on graph preprocessing

A path planning and preprocessing technology, applied in two-dimensional position/channel control, vehicle position/route/height control, non-electric variable control, etc., can solve the problem of non-optimal planning path and A* algorithm neighborhood search efficiency low level problem

Pending Publication Date: 2021-08-31
BEIHANG UNIV
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Problems solved by technology

[0006] In order to solve the problems of low search efficiency of A* algorithm neighborhood and non-optimal planning path, the present invention proposes an improved method of A* algorithm based on graph preprocessing algorithm

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  • Path planning method of improved A* algorithm based on graph preprocessing
  • Path planning method of improved A* algorithm based on graph preprocessing
  • Path planning method of improved A* algorithm based on graph preprocessing

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Embodiment Construction

[0018] 5.1 Map preprocessing

[0019] 5.1.1 Map Segmentation

[0020] (1) Transform multi-connected concave polygons into single-connected concave polygons

[0021] A map containing obstacles can usually be regarded as a multi-connected concave polygon. In this paper, a virtual auxiliary line connecting obstacles and map boundary vertices is introduced to transform the multi-connected concave polygon into a single-connected concave polygon. Such as image 3 As shown, when the map M 1 m 2 …M n There is an obstacle O in 1 o 2 …O n , choose a point O of the obstacle i A certain vertex M on the boundary of the map i connection, denoted as O i m i . Its vector can have two directions with Assuming two vectors and There is a distance ΔD→0 between them, and the vertex O of the obstacle i Vertex M of the map with i Connected by two vectors, the map becomes a simply connected domain map M 1 m 2 …M i o i o i+1 …O n o 1 …O i m i …M n .

[0022] If there a...

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Abstract

The invention discloses a path planning method of an improved A* algorithm based on graph preprocessing. Due to problems of complexity of map modeling and the like, path-finding efficiency is greatly reduced (as shown in Figure 1) due to large calculation amount and high redundancy of a traditional A* algorithm, and a large amount of performance consumption is caused. Due to the limitation of neighborhood search in a grid map, the traditional A * algorithm cannot actually realize the optimal path in the global sense. In order to solve the problems, firstly, an improved Maklink graph method is used for decomposing a free space on a map into a plurality of convex polygon areas, then all the areas are coded into feature nodes, finally, an optimal area channel is solved based on the principle of an A * algorithm, and a globally optimal path solution is obtained in the channel. The problems that a traditional A * algorithm is low in neighborhood search efficiency, the planned path is not optimal and the like are solved, and compared with other common algorithms, the proposed algorithm has remarkable advantages in the aspects of planning speed, path length, stability, completeness and the like.

Description

[0001] 1. Technical field [0002] The invention relates to the field of path planning, in particular to a path planning method based on graphics and heuristic search. [0003] 2. Background technology [0004] Autonomous driving technology is a hot topic in the field of artificial intelligence. In the future society, most vehicles will be equipped with autonomous driving technology, which will make the ground traffic smoother and the traffic accident rate lower. The path planning algorithm is a key part of it. The so-called mobile robot path planning, its goal is to independently find an optimal barrier-free travel route from the starting position to the target position in a known or unknown working environment, following certain constraints and criteria. As a classic path planning algorithm, the A* (A star) algorithm introduces a heuristic function based on the Dijkstra algorithm, so that it can approach the target node faster and find a better path. However, as the complex...

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0217G05D1/0221
Inventor 李昭莹石若凌
Owner BEIHANG UNIV
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