蚁群优化算法
运动规划
数学优化
启发式
趋同(经济学)
计算机科学
路径(计算)
势场
领域(数学)
蚁群
机器人
元启发式
算法
粒子群优化
旅行商问题
最短路径问题
遗传算法
启发式
最优化问题
人工智能
群体智能
数学
经济
地质学
程序设计语言
纯数学
经济增长
地球物理学
作者
Hui Wang,Zheng' An Wang,Li Yu,Xueying Wang,Chaoda Liu
出处
期刊:Chinese Control Conference
日期:2018-07-01
被引量:7
标识
DOI:10.23919/chicc.2018.8483844
摘要
An ant colony optimization with improved potential field algorithm for robot path planning is proposed in this paper. Potential field resultant is used as a kind of heuristic for finding a path. The improved algorithm makes the advantages of potential field and ant colony algorithm in different stages of program operation and shows good features in searching for the optimal path. The length optimal or suboptimal path can always be found in different environments. Simulation results showed that the improved algorithm has higher convergence speed compared to the general ant colony algorithm, it also has a pretty good global searching ability.
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