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:在本文中, 我们提出一个路径再规划算法, 使机器人能够在移动障碍的情况下工作。 算法在一组预先计算过的路径之间开关, 以避免与移动障碍发生碰撞。 它还可以随时改善当前路径。 使用知情抽样可以提高搜索速度。 数字结果显示策略在不同模拟假设中的有效性 。