Multi-Objective Safe-Interval Path Planning With Dynamic Obstacles
Multi-Objective Safe-Interval Path Planning With Dynamic Obstacles
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DOI：
10.1109/lra.2022.3187270
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发表时间：
2022-07-01
影响因子：
5.2
通讯作者：
Choset, Howie
中科院分区：
文献类型：
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作者：
Ren, Zhongqiang;Rathinam, Sivakumar;Choset, Howie
动态障碍之间的路径规划是具有许多应用的机器人技术中的一个基本问题。在这项工作中，我们调查了一个具有动态障碍（MOPPWDO）的称为多目标路径计划的问题，该问题需要在沿着已知轨迹移动的同时优化多个冲突的目标，例如到达时间，通信，通信，通信，通信，通信，通信，通信，交流，通信，交流，通信，交流，通信，通信，通信，通信，遇到无碰撞的帕累托最佳路径。稳健性和障碍清除。大多数现有的多目标A*类似计划者都认为没有动态障碍，并且天真地应用它们来解决MOPPWDO可以导致大量计算时间。另一方面，有效的算法（例如安全间隔路径平面图（SIPP））可以处理动态障碍，但对于一个目标。在这项工作中，我们通过利用SIPP的安全间隔概念来开发一种称为Mo-Sipp的算法，以在存在动态障碍的情况下有效地表示搜索空间，又是来自多目标A*算法的搜索技术。我们表明，Mo-Sipp可以保证找到整个帕累托最佳的前部，并使用两个目标和三个目标进行广泛的数值测试验证Mo-Sipp。结果表明，MO-SIPP的运行速度比常规替代方案快。
Path planning among dynamic obstacles is a fundamental problem in Robotics with numerous applications. In this work, we investigate a problem called Multi-Objective Path Planning with Dynamic Obstacles (MOPPwDO), which requires finding collision-free Pareto-optimal paths amid obstacles moving along known trajectories while simultaneously optimizing multiple conflicting objectives, such as arrival time, communication robustness and obstacle clearance. Most of the existing multi-objective A*-like planners consider no dynamic obstacles, and naively applying them to address MOPPwDO can lead to large computation times. On the other hand, efficient algorithms such as Safe-Interval Path Planing (SIPP) can handle dynamic obstacles but for a single objective. In this work, we develop an algorithm called MO-SIPP by leveraging both the notion of safe intervals from SIPP to efficiently represent the search space in the presence of dynamic obstacles, and search techniques from multi-objective A* algorithms. We show that MO-SIPP is guaranteed to find the entire Pareto-optimal front, and verify MO-SIPP with extensive numerical tests with two and three objectives. The results show that the MO-SIPP runs up to an order of magnitude faster than the conventional alternates.