In this paper, we propose a path re-planning algorithm that makes robots able to work in scenarios with moving obstacles. The algorithm switches between a set of pre-computed paths to avoid collisions with moving obstacles. It also improves the current path in an anytime fashion. The use of informed sampling enhances the search speed. Numerical results show the effectiveness of the strategy in different simulation scenarios.

翻译：本文提出一种路径重规划算法，使机器人能够在存在移动障碍物的场景中工作。该算法在预先计算的一组路径之间切换，以避免与移动障碍物发生碰撞，同时以任意时间方式持续改进当前路径。知情采样的运用提升了搜索速度。数值结果表明该策略在不同仿真场景中均具有有效性。