实时规划算法，让机器人在动态环境里更快更稳地避障行进。
Real-Time Fast Marching Tree for Mobile Robot Motion Planning in Dynamic Environments
- 结合FMT*与RT-RRT*，实时生成全局路径和可立即执行的局部路径。
- 动态重连树结构，避免路径进入障碍物，支持多次复用同一棵树规划不同目标。
- 仿真显示：提前执行局部路径能显著缩短到达时间，即使有走错风险。
本文提出一种实时快速行进树（RT-FMT）规划算法，具备局部与全局路径生成、多目标查询及动态障碍物避让能力。搜索过程中，RT-FMT快速寻找全局解的同时，生成可立即执行的局部路径，使机器人能尽早启动运动。此外，算法持续重连树结构，防止分支进入动态障碍物，并保持树根靠近机器人，从而支持多次复用以规划不同目标。该算法基于FMT*与实时快速探索随机树（RT-RRT*）。仿真表明，多数情况下RT-FMT在执行代价和到达时间上优于RT-RRT*。同时，仿真还证明：在全局路径未生成前即执行局部路径，虽存在走劣路径的小概率，但能有效减少总到达时间。
原文摘要 · Abstract (English)
This paper proposes the Real-Time Fast Marching Tree (RT-FMT), a real-time planning algorithm that features local and global path generation, multiple-query planning, and dynamic obstacle avoidance. During the search, RT-FMT quickly looks for the global solution and, in the meantime, generates local paths that can be used by the robot to start execution faster. In addition, our algorithm constantly rewires the tree to keep branches from forming inside the dynamic obstacles and to maintain the tree root near the robot, which allows the tree to be reused multiple times for different goals. Our algorithm is based on the planners Fast Marching Tree (FMT*) and Real-time Rapidly-Exploring Random Tree (RT-RRT*). We show via simulations that RT-FMT outperforms RT- RRT* in both execution cost and arrival time, in most cases. Moreover, we also demonstrate via simulation that it is worthwhile taking the local path before the global path is available in order to reduce arrival time, even though there is a small possibility of taking an inferior path.
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