Path planning of mobile robots based on an improved A*algorithm

Abstract

When an AGV (Automated Guided Vehicle) performs navigation tasks, it needs to run the path planning algorithm to obtain an optimal path in a current environment. In this paper, Dijkstra algorithm and A*algorithm with different heuristic functions are applied to static environment modeling with various types of obstacles. To solve the problem that there are many redundant points and inflection points in the search process of the A*algorithm, an improved A*algorithm with Manhattan distance as a heuristic function is selected as the path planning algorithm. In addition, a calculation method of optimizing a past cost function is proposed, and the weight of heuristic function is optimized simultaneously. Simulation results show that the improved algorithm has a higher efficiency and less path inflection points than the traditional A*algorithm has.