When unmanned equipment performs tasks such as fixed-point patrol and cargo handling,it is necessary to solve the problem of multi-point traversal with obstacle avoidance path planning.This paper studies a global path planning algorithm based on improved Maklink graph to optimize the obstacle avoidance path with strong stability.Firstly,improved Maklink graph is established as the space model to simplify the work space.Then,an improved ant colony algorithm is designed to plan the path in the above space model.The algorithm adopts the heuristic function for multi-point traversal,tabu search,local optimal processing mechanism and elite individual retention and additional evolution strategy.Finally,comparative experiments show that the proposed algorithm is effective,has better optimization ability and stronger stability in different task environments.Compared with the probabilistic roadmap-based algorithm and the traditional ant colony algorithm in 10 cases,the improvement in path length optimization can reach 21.13%and 49.31%maximally,and the stability improvement can reach 99.56%and 99.82%maximally.
维普
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