Map Path Planning Method Based on Improved Ant Colony Algorithm and Its Application
With the development of science and technology and the continuous progress of society,how to improve the convergence effect and accuracy of path planning algorithm has gradually become a research hotspot.When the existing ant colony algorithm is planning the path,it often encounters the problem that it is difficult to get the optimal solution locally.Therefore,in this paper,the heuristic pheromone updating strategy is used to improve the search ability of ant colony algorithm,and the optimal parameters are obtained by adaptive parameter adjustment method to form an improved ant colony algorithm.The optimized algorithm is applied to the Oliver30,Att48 and Eil51 open data sets,and the experimental results are compared with the existing path planning algorithms.The results show that the proposed algorithm can plan the optimal path with relatively little iteration,indicating that the optimization algorithm can get the optimal solution quickly and has a good ability to search the optimal path.
ant colony algorithmdynamic updating mechanism of pheromonemap path planningalgorithm optimization
NETL
NSTL
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