一种人工势场导向的蚁群路径规划算法

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z11): 47-50.

一种人工势场导向的蚁群路径规划算法

王芳,李昆鹏,袁明新

西安航空学院航空工程系西安710077;长安大学机械学院西安710064;江苏科技大学机电与汽车工程学院张家港215600

出版日期:2018-11-14 发布日期:2018-11-14

AntColony Algorithm Based on Optimization of Potential Field Method for Path Planning

WANG Fang,LI Kun-peng and YUAN Ming-xin

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 针对复杂环境下的机器人路径规划问题,提出一种势场法优化的蚁群路径规划算法。为提高算法收敛速度,将人工势场法的规划结果作为先验知识,对蚁群初始到达的栅格进行邻域信息素的初始化,并通过构建势场导向权改变蚂蚁概率转移函数,使其作用于蚂蚁路径搜索的始终,从而改善蚁群路径搜索的盲目性。仿真结果表明,新算法具有收敛速度快、规划路径短以及环境自适应的优点。

关键词: 路径规划,蚁群算法,人工势场,转移概率,导向权

Abstract: To realize path planning in complicated environments,a new potential field optimal ant colony algorithm for path planning was presented.To further quicken the convergence speed of AC,the path planning results of potential field method were taken as the prior knowledge,and the original reached grids were initialized by neighborhood pheromone.The potential field guided weight was constructed to change transition probability as well,thus it can be active over the entire period of path searching,and can get rid of blindness.Simulation results indicate that the proposed algorithm(APF-AC) is characterized by high convergence speed,short planning path and self-adaptive.

Key words: Path planning,Ant colony algorithm,Artificial potential field,Transition probability,Guided weight computer

王芳,李昆鹏,袁明新. 一种人工势场导向的蚁群路径规划算法[J]. 计算机科学, 2014, 41(Z11): 47-50. https://doi.org/

WANG Fang,LI Kun-peng and YUAN Ming-xin. AntColony Algorithm Based on Optimization of Potential Field Method for Path Planning[J]. Computer Science, 2014, 41(Z11): 47-50. https://doi.org/

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