摘要
为活动机器人计划的即时全球性最佳的路径的一个新奇方法基于蚂蚁殖民地系统(交流) 被建议算法。这个方法包括三步：第一步正在利用 MAKLINK 图理论建立活动机器人的空间模型，第二步正在利用 Dijkstra 算法发现一条非最优的没有碰撞的路径，并且第三步正在利用 ACS 算法优化非最优的路径的地点以便产生全球性最佳的路径。建议方法是有效的并且能在即时路径被使用活动机器人计划的计算机模拟实验表演的结果。建议方法比与优秀人材模型一起基于基因算法计划方法的路径处于集中速度，答案变化，动态集中行为，和计算效率有更好的性能，这被验证了。
A novel method for the real-time globally optimal path planning of mobile robots is proposed based on the ant colony system （ACS） algorithm. This method includes three steps： the first step is utilizing the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is utilizing the Dijkstra algorithm to find a sub-optimal collision-free path, and the third step is utilizing the ACS algorithm to optimize the location of the sub-optimal path so as to generate the globally optimal path. The result of computer simulation experiment shows that the proposed method is effective and can be used in the real-time path planning of mobile robots. It has been verified that the proposed method has better performance in convergence speed, solution variation, dynamic convergence behavior, and computational efficiency than the path planning method based on the genetic algorithm with elitist model.
出处
《自动化学报》
EI
CSCD
北大核心
2007年第3期279-285,共7页
Acta Automatica Sinica
基金
Supported by National Natural Science Foundation of P.R.China(50275150)
National Research Foundation for the Doctoral Program of Higher Education of P.R.China(20040533035)
关键词
蚁群系统
运算法则
自动化系统
计算机技术
Mobile robot, globally optimal path planning,ACS algorithm, MAKLINK graph, Dijkstra algorithm
