Focs: Planning By Fusion Of Optimal Control & Search And Its Application To Navigation

2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)(2018)

引用 1|浏览16
暂无评分
摘要
Both Optimal Control and Search-based Planning are used extensively for path planning and have their own set of advantages and disadvantages. In this paper, we propose an algorithm FOCS (Fusion of Optimal Control and Search) that combines these two classes of approaches together. FOCS finds a path exploiting the advantages of both approaches while providing a bound on the sub-optimality of its solution. The returned path is a concatenation of the path found in the implicit graph constructed by search and the path generated by following the negative gradient of the value function obtained as a solution of the Hamilton-Jacobi-Bellman equation. We analyze the algorithm and illustrate its effectiveness in finding a minimum-time path for a car-like vehicle in different environments.
更多
查看译文
关键词
car-like vehicle,Hamilton-Jacobi-Bellman equation,FOCS,minimum-time path,returned path,sub-optimality,path planning,Search-based Planning,Optimal Control & Search
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要