计算机工程与应用2016，Vol.52Issue(11)：38-43,6.DOI:10.3778/j.issn.1002-8331.1406-0339
机器人全局路径规划的混合蚁群系统算法
Hybrid ACS algorithm for robot global path planning
摘要
Abstract
To solve the contradictory between the convergence speed and the local optimum, a hybrid ACS algorithm for robot global path planning problem is presented. The algorithm consists of a combination of Dijkstra algorithm for finding a sub-optimal free path and an improved ACS algorithm for optimizing the sub-optimal path. Then, it defines a new heuris-tic information function which increases the population diversity and a modified crossover operator for avoiding getting trapped in the local optimum and improving the solution quality. The results of simulation experiments confirm that the proposed algorithm is effective and has better performance in solution quality and search efficiency as compared with the path planning method in the literature. It is observed that the hybrid ACS algorithm can find better target traversal paths and spend less time with faster convergence speed for multi-target path planning problems in the complex environment.关键词
全局路径规划/蚁群系统算法/Dijkstra算法/启发信息函数/多目标点Key words
global path planning/ant colony system/Dijkstra algorithm/heuristic information function/multi-target分类
信息技术与安全科学引用本文复制引用
吕金秋,游晓明,刘升..机器人全局路径规划的混合蚁群系统算法[J].计算机工程与应用,2016,52(11):38-43,6.基金项目
国家自然科学基金(No.61075115) （No.61075115）
上海市教委科研创新重点项目基金(No.12ZZ185) （No.12ZZ185）
上海市学科专业建设项目(No.XKCZ1212). （No.XKCZ1212）
