Robot path planning method fusing bidirectional search mechanism and improved A* algorithm

Abstract

The invention discloses a robot path planning method fusing a bidirectional search mechanism and an improved A * algorithm. The method aims at solving the problems that a path planned through an A * algorithm has the risk of touching obstacles, and too many redundant points and turning points are generated. The improved A * algorithm fused with the bidirectional search mechanism is provided, firstly, a search direction positioning strategy is introduced, node search is reduced, and algorithm efficiency is improved; secondly, an improved child node expansion strategy is added, so that a safe distance is kept between the robot and the obstacle; a bidirectional search mechanism is fused, and an improved A * algorithm is utilized to search at a target point and a starting point at the same time, so that the planning time is further shortened. An initial path is obtained in a two-dimensional grid map environment, a path turning point is extracted through a vertical distance limit value method, a greedy thought is introduced to select an optimal turning point, the optimal turning point is fitted based on a B spline curve, and a smooth path is obtained. According to the method, the optimal path which is short in time consumption, free of touch and few in turning points can be found.

Description

technical field [0001] The invention relates to the field of robot control, in particular to a robot path planning method integrating a bidirectional search mechanism and an improved A* algorithm. Background technique [0002] The ultimate goal of mobile robot path planning is to find a safe, collision-free path from the starting point to the target point. On this basis, we also need to solve how to spend the shortest time and the lowest cost to find the optimal path with the shortest distance. [0003] At present, the commonly used path planning algorithms include artificial potential field method, A* algorithm, dynamic window algorithm, genetic algorithm, ant colony algorithm, etc. Among them, the A* algorithm is widely used in static global path planning because of its simplicity, high efficiency, easy operation, and accuracy. The A* algorithm combines the advantages of BFS (breadth-first search) and Dijkstra algorithm. While performing heuristic search to improve the e...

AI Technical Summary

Problems solved by technology

However, the traditional A* algorithm does not take into account the safe distance between the robot and the obstacle, the planned path often fits the edge of the obstacle, there are many turning points in the path, the overall path is not smooth, and the path planning time is long, which is not conducive to the robot exercise

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