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Multi-robot Path Planning with the Spatio-Temporal A~* Algorithm and Its Variants

机译:时空A〜*算法的多机器人路径规划及其变体

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This paper presents the design of an offline collision-free path planning algorithm for multiple mobile robots travelling simultaneously on a 2D gridded map. We first solved this problem by extending the traditional A~* algorithm into 3D, namely two spatial and one time dimensions. This 3D approach is proved computationally costly and this led to the development of a novel and faster Spatio-Temporal (S-T) A~* algorithm. This is a modified A~* algorithm, which uses discrete time stamps and a temporal occupancy table to communicate previously planned routes and potential collision among robots. We further adapted the S-T A~* algorithm to allow robots to stop and wait near nodes where potential collision is detected in order to increase their probability of finding a viable path to their destination. Using a time-based objective function that requires all robots in the environment to reach their respective destination in the shortest possible time, this decoupled planning strategy was done using a fixed priority based on the slowest robot first. Another variant using an adaptive priority scheme was then introduced to improve the success rate of finding a viable path for all robots as the number of robots in the fixed-sized environment increased. We present experimental results comparing the performance of the various path planning and priority schemes.
机译:本文提出了一种离线的无碰撞路径规划算法的设计,该算法用于多个在二维网格地图上同时移动的移动机器人。我们首先通过将传统的A〜*算法扩展到3D(即两个空间和一个时间维度)来解决此问题。这种3D方法在计算上被证明是昂贵的,这导致了一种新颖,更快的时空(S-T)A〜*算法的发展。这是一种经过改进的A〜*算法,该算法使用离散时间戳和时间占用表来传达先前计划的路线和机器人之间的潜在碰撞。我们进一步调整了S-T A〜*算法,以允许机器人在检测到潜在碰撞的节点附近停止并等待,以增加其找到通往目的地的可行路径的可能性。使用基于时间的目标函数,该函数要求环境中的所有机器人都在最短的时间内到达各自的目的地,因此,这种解耦的规划策略是首先基于最慢的机器人使用固定优先级来完成的。然后引入了使用自适应优先级方案的另一种变体,以随着固定大小环境中机器人数量的增加,提高为所有机器人找到可行路径的成功率。我们目前的实验结果比较了各种路径规划和优先级方案的性能。

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