摘要
论文提出一种新的群集智能算法,在用Dijkstra算法基于链接图建模的地图中得到一个最优解的可行空间后,再用粒子群算法或蚂蚁算法优化得到全局的最优路径。因为群集智能算法是一种概率搜索算法,没有集中控制约束条件,不会因为个别个体的故障影响整个问题的求解,具有较强的鲁棒性,所以在机器人全局路径规划应用中具有较显著的优点。仿真结果表明了算法的有效性,是机器人路径规划的一个较好的方法。
This work mainly deals with the application of a swarm intelligent algorithm in the field of mobile robot＇s path planning.The algorithm is a probabilistic searching method,which is from the traditional swarm intelligent ideas,and characterized by its parallel and distributed features.A novel optimization is presented in this paper,which Dijkstra algorithm is firstly adopted to get a best-solution space,then two basic swarm optimization algorithms：ant colony optimization（ACO） and particle swarm optimization（PSO） are analyzed and contrasted in detail.In the end of the paper,some corresponding experimental results are given,to prove the effectiveness of the swarm intelligent algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第5期52-55,共4页
Computer Engineering and Applications
