摘要
移动机器人在未知的、动态的环境中进行路径规划必须考虑到环境地图构建的不完备性和算法的实时性。针对这种情况,提出了一种基于启发式拓展距离转化的移动机器人路径规划算法。算法在未知的环境中,通过启发信息和实时探测静止或移动的障碍物信息构建不完备的栅格地图,对移动的障碍物采用延后处理策略,实时地搜索最优路径并驱动机器人运动到目标点。当发生下降阻碍时,则仅对需要的范围传播权值变更信息。算法适用于大范围的时变环境,并具有良好的收敛性。仿真实验验证了算法可行性和正确性。
The task of planning path for a mobile robot in unknown dynamic environment has received considerable attention in the robot research. More attention must be paid to the non-completeness of terrain map and the real-time of algorithm. A novel algorithm, heuristic-exploring distance transform （HEDT） is presented, capabled of planning shortest path in unknown dynamic vast environment. The algorithm constructs non- completeness from sensor data and heuristic information, applies delay-deal strategy for moving obstacle and find a optimal descend path to drive robot moving. When there is no descend path, the algorithm just posts the information to required areas. The algorithm has good convergence and can effectively used in unknown dynamic vast environment. The result of simulation proves the feasibility and validity of this algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2008年第10期1973-1976,F0003,共5页
Systems Engineering and Electronics
基金
国家自然科学基金(60775058)
教育部科学技术研究重点项目基金(107028)资助课题
关键词
移动机器人
路径规划
未知动态环境
启发式拓展距离转化
mobile robot, path planning
unknown dynamic environment
heuristic-exploring distance transform
