通过大量安全盒子的集合进行快速路径规划
Fast Path Planning Through Large Collections of Safe Boxes
AI总结：
提出一种基于加权图最短路径和凸最优控制的快速算法，在大量轴对齐安全盒子集合中生成始终安全的平滑轨迹，并能检测不可行性，附开源实现。
摘要：
我们提出了一种快速算法，用于设计受限于位于轴对齐盒子集合中的平滑路径（或轨迹）。我们考虑这些安全盒子数量巨大的情况，并且对它们的基本预处理（如寻找它们的交集）可以离线完成。在运行时，我们能在给定的初始和终端位置之间快速生成平滑路径。我们的算法设计出的轨迹保证始终安全，并在不存在此类轨迹时检测不可行性。我们的算法基于两个可以高效求解的子问题：在加权图中寻找最短路径，以及求解（多个）凸最优控制问题。我们在大规模数值示例上演示了所提出的路径规划器，并提供了高效的开源软件实现 fastpathplanning。
英文摘要：
We present a fast algorithm for the design of smooth paths (or trajectories) that are constrained to lie in a collection of axis-aligned boxes. We consider the case where the number of these safe boxes is large, and basic preprocessing of them (such as finding their intersections) can be done offline. At runtime we quickly generate a smooth path between given initial and terminal positions. Our algorithm designs trajectories that are guaranteed to be safe at all times, and detects infeasibility whenever such a trajectory does not exist. Our algorithm is based on two subproblems that we can solve very efficiently: finding a shortest path in a weighted graph, and solving (multiple) convex optimal-control problems. We demonstrate the proposed path planner on large-scale numerical examples, and we provide an efficient open-source software implementation, fastpathplanning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
