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Research on Robot Path Planning Based on Improved Adaptive Ant Colony Algorithm

Shao Xiao-Qiang, Zhichao Lv, Xuan Zhao, Xinchao Nie

发表年份
2019
引用次数
8

摘要

Aiming at the problem that ant colony algorithm is easy to fall into local optimal and slow convergence in robot path planning, a path planning method based on improved ant colony algorithm is proposed for static obstacle environment.This method improves the search efficiency of the algorithm by using the adaptive adjustment heuristic function; The attenuation coefficient is adjusted dynamically to accelerate the convergence speed of the algorithm based on ant colony rule, pheromone is updated and the maximum and minimum of pheromone concentration is limited.Simulation results show that compared with other algorithms in the same environment, the improved algorithm has a faster convergence rate when the path planning results are the same.The improved algorithm has obtained the optimal path in different complexity environments, which also shows the effectiveness and reliability of the algorithm.

关键词

Ant colony optimization algorithmsMotion planningComputer sciencePath (computing)RobotArtificial intelligenceMobile robotComputer network

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