一种障碍环境下机器人路径规划的蚁群粒子群算法-控制理论与应用.PDFVIP

26 8 Vol. 26 No. 8 2009 8 Control Theory Applications Aug. 2009 :2009 , , (, 450001) : , . , , , , ; , , , . , . : ; ; ; : TP242.6 : A Ant colony optimization and particle swarm optimization for robot-path planning in obstacle environment DENG Gao-feng ZHANG Xue-ping LIU Yan-ping (School of Information Science and Engineering, Henan University of Technology, Zhengzhou Henan 450001, China) Abstract: For searching the best path for a robot in an obstacle environment, this paper proposes an algorithm of ant colony optimization(ACO) and particle swarm optimization(PSO) for path planning. The new algorithm effectively combines the advantages of ACO and PSO. It adopts the grid method for environment modeling and makes use of the efficiency and succinctness of PSO to obtain the initial distribution of pheromone, reducing the number of iterations and accelerating the convergence. At the same time, by using the parallelizability of ants and distributed parallelized-searching technology, the performance of the algorithm is effectively improved. The simulation result shows the effectiveness of the proposed algorithm in solving the problem of path planning. Key words: path planning; obstacle environment; ant colony optimization; particle swarm optimization 1 (Introduction) . , . , . , (ACO) , , Dorigo M, Maniezzo VColorni , A2090.