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T* : A Heuristic Search Based Path Planning Algorithm for Temporal Logic Specifications

机译:T *:基于启发式搜索的时态逻辑路径规划算法

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The fundamental path planning problem for a mobile robot involves generating a trajectory for point-to-point navigation while avoiding obstacles. Heuristic-based search algorithms like A* have been shown to be efficient in solving such planning problems. Recently, there has been an increased interest in specifying complex path planning problem using temporal logic. In the state-of-the-art algorithm, the temporal logic path planning problem is reduced to a graph search problem, and Dijkstra's shortest path algorithm is used to compute the optimal trajectory satisfying the specification.The A* algorithm, when used with an appropriate heuristic for the distance from the destination, can generate an optimal path in a graph more efficiently than Dijkstra's shortest path algorithm. The primary challenge for using A* algorithm in temporal logic path planning is that there is no notion of a single destination state for the robot. We present a novel path planning algorithm T* that uses the A* search procedure opportunistically to generate an optimal trajectory satisfying a temporal logic query. Our experimental results demonstrate that T* achieves an order of magnitude improvement over the state-of-the-art algorithm to solve many temporal logic path planning problems in 2-D as well as 3-D workspaces.
机译:移动机器人的基本路径规划问题涉及到生成点对点导航的轨迹,同时避开障碍物。事实证明,基于启发式的搜索算法(例如A *)在解决此类计划问题方面非常有效。最近,人们对使用时间逻辑指定复杂路径规划问题的兴趣日益浓厚。在最先进的算法中,时间逻辑路径规划问题简化为图搜索问题,并且Dijkstra的最短路径算法用于计算满足规范的最佳轨迹。对距目的地的距离进行适当的启发式搜索,可以比Dijkstra的最短路径算法更有效地在图形中生成最佳路径。在时态逻辑路径规划中使用A *算法的主要挑战是机器人没有单一目标状态的概念。我们提出了一种新颖的路径规划算法T *,该算法使用A *搜索过程来时机生成满足时间逻辑查询的最优轨迹。我们的实验结果表明,T *与最新算法相比,可解决2D以及3D工作空间中的许多时间逻辑路径规划问题,从而实现了一个数量级的改进。

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