计算机工程与应用Issue(22)：33-37,5.DOI:10.3778/j.issn.1002-8331.1502-0047
改进的势场蚁群算法的移动机器人路径规划
Improved ant colony optimization with potential field heuristic for robot path planning
摘要
Abstract
In view of the shortcomings of traditional ant colony algorithm are searching unreasonable, the converge slowly and getting into local solutions easily for the differential concentration of pheromone is small and the positive feedback have not obvious effect. The potential force of artificial potential field algorithm can guide the robot to the goal position, a kind of ant colony optimization with potential field heuristic, modeling the environment with grid method, the potential force, the potential force-influence coefficient and the distance between the robot and the goal are utilized to construct comprehensive heuristic information, ant colony algorithm mechanism is used to search a path in an unknown environment, many simulation results show ant colony optimization with potential field heuristic can find a shorter path and the con-verges fast.关键词
人工势场算法/蚁群算法/移动机器人/路径规划Key words
artificial potential/ant colony algorithm/robot/path planning分类
信息技术与安全科学引用本文复制引用
曾明如,徐小勇,刘亮,罗浩,徐志敏..改进的势场蚁群算法的移动机器人路径规划[J].计算机工程与应用,2015,(22):33-37,5.基金项目
国家自然科学基金（No.614663032）；江西省科技厅项目（Nol20141BBA10035）。 （）
