摘要
针对未知环境中空中机器人路径规划问题,提出了一种适用于静态未知环境的路径规划方法。该方法在概率路线图法基础上,重新设计了在线重规划阶段,使得空中机器人不需更新整个规划空间,而是借助传感器感知环境信息,重构局部路线图,从而达到避障的目的。该方法可在规划空间中搜索出一条光滑的且能有效避开障碍物的可行路径。仿真结果表明,该方法复杂度低、实时性好,能快速规划出静态未知环境下空中机器人的可行路径。
In view of the aerial robots path planning problem in unknown environment, this paper proposed a path planning method for the static unknown environment. Based on the probabilistic roadmap method, the method redesigned the online replanning stage, and perceived its environment thought sensors, and used sensors＇ information to reconstruct the local roadmap. Thus it can make the aerial robots avoid the obstacle effectively and search out a smooth feasible path in configuration space without update the whole planning space. The simulation results show that this method have low complexity, good real-time performance and it can plan out a feasible path rapidly for aerial robots in static unknown environments.
出处
《航空科学技术》
2016年第4期69-73,共5页
Aeronautical Science & Technology
基金
贵州民族大学引进人才科研基金资助项目(15XRY007)~~
关键词
未知环境
概率路线图
空中机器人
路径规划
unknown environment
probabilistic roadmap
aerial robots
path planning
