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题名: Improved ant colony optimization algorithm and its application on path planning of mobile robot
作者: Zhao JP(赵娟平) ; Fu XH(符秀辉)
作者部门: 机器人学研究室
关键词: Artificial intelligence ; Mobile robots ; Motion planning ; Optimization
刊名: Journal of Computers
ISSN号: 1796-203X
出版日期: 2012
卷号: 7, 期号:8, 页码:2055-2062
收录类别: EI
产权排序: 2
摘要: This paper uses the grid method with coding tactic based on effective vertexes of barriers (EVB-CT-GM) as the method of environment modeling and ant colony optimization algorithm with two-way parallel searching strategy (TWPSS-ACOA) is adopted to accelerate searching speed. In view of that the TWPSS-ACOA has the defects of losing some feasible paths and even optimal paths because of its ants meeting judgment strategy (AMJS), so a new AMJS is proposed. Then a new method to rationally distribute initial pheromone is given to accelerate convergence speed of initial stages of ACO algorithm. Later, in order to avoid running into local optima and to speed up optimization process, a new path selecting method and a new global pheromone updating technique are put forward. Finally simulation researches of path planning of mobile robot based on improved TWPSS-ACOA are made under different two-dimension environments and simulation results show the improved algorithm can find safe paths at higher convergence speed even in complex environment.
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/10631
Appears in Collections:机器人学研究室_期刊论文

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