The paper presents an algorithm, called Self- Morphing Anytime Replanning Tree (SMART), that facilitates anytime replanning in dynamic environments. SMART performs risk-based tree-pruning if its current path is obstructed by nearby moving obstacle(s), resulting in multiple disjoint subtrees. Then, for speedy recovery, it exploits these subtrees and performs informed tree-repair at hot-spots that lie at the intersection of subtrees to find a new path. The performance of SMART is comparatively evaluated with seven existing algorithms through extensive simulations. Two scenarios are considered with: 1) dynamic obstacles and 2) both static and dynamic obstacles. The results show that SMART yields significant improvements in replanning time, success rate and travel time. Finally, the performance of SMART is validated by a real laboratory experiment.

翻译：本文提出了一种名为自变形随时重规划树（SMART）的算法，用于在动态环境中实现随时重规划。当当前路径被附近移动障碍物遮挡时，SMART执行基于风险的树修剪，形成多个不相交子树。随后，为快速恢复，该算法利用这些子树，在子树交叉处的热点区域进行有依据的树修复以寻得新路径。通过大量仿真实验，将SMART与七种现有算法进行了性能对比评估。研究考虑了两种场景：1）动态障碍物；2）静态与动态障碍物并存。结果表明，SMART在重规划时间、成功率和行程时间上均有显著提升。最后，通过真实实验室实验验证了SMART的性能。