摘要
目的提出一种基于障碍物特征点的移动机器人全局路径规划算法,克服传统全局路径规划算法信息存储量大,计算量大,规划速度慢的缺点.方法通过膨胀原理建立环境地图,只记录障碍物的特征点,减少了算法信息的存储量.然后采用最大最小原则,逐步搜索子目标点,最终到达目标.结果该算法能以最小的距离代价逐步绕过当前距离机器人最近的障碍物,并能保证搜索到的路径是安全有效的.结论笔者所提算法简单,计算量小,仿真实验验证了算法的有效性.
A new global path planning algorithm based on feature points of obstacles is proposed, which overcomes the disadvantage of the traditional method that stores a great amount of information and plans slowly. The environmental map is established according to the principle of expansion, which just records the feature points of obstacles. This method greatly reduces the amount of information storage. Then the maxmin principle is used to search sub-goal points till it reaches the goal. The algorithm can cost a minimum distance to bypass the obstacle which is nearest from robot, and guarantee the path is safe and valid. The algorithm is simple, and the simulation results show the algorithm is valid.
出处
《沈阳建筑大学学报（自然科学版）》
CAS
北大核心
2009年第6期1212-1216,共5页
Journal of Shenyang Jianzhu University：Natural Science
基金
建设部基金项目(2007-K8-7)
