3D动态环境实时路径重规划，树结构自变形避障
SMART-3D: Three-Dimensional Self-Morphing Adaptive Replanning Tree
- 用热点节点替代网格分解，实现3D环境高效路径重构
- 在动态障碍物场景中成功率高，重规划时间低于10毫秒
- 适合无人机、机器人等需要实时避障的嵌入式系统
本文提出SMART-3D，是SMART算法在3D环境中的扩展。该算法基于树结构，在存在快速移动障碍物的动态环境中实现自适应重规划。当当前路径被阻挡时，SMART-3D会实时对底层树结构进行形态变换，以找到新路径。通过将原算法中的热点区域概念替换为热点节点，彻底摆脱了网格分解需求，从而显著提升计算效率并支持3D扩展。热点节点可高效连接，使树结构能快速重构出安全可靠的路径。在包含随机移动动态障碍物的2D与3D仿真环境中进行了大量测试，结果表明，SMART-3D具备高路径成功概率和低重规划延迟（<10毫秒），证明其适用于实时车载或机载应用。
原文摘要 · Abstract (English)
This paper presents SMART-3D, an extension of the SMART algorithm to 3D environments. SMART-3D is a tree-based adaptive replanning algorithm for dynamic environments with fast moving obstacles. SMART-3D morphs the underlying tree to find a new path in real-time whenever the current path is blocked by obstacles. SMART-3D removed the grid decomposition requirement of the SMART algorithm by replacing the concept of hot-spots with that of hot-nodes, thus making it computationally efficient and scalable to 3D environments. The hot-nodes are nodes which allow for efficient reconnections to morph the existing tree to find a new safe and reliable path. The performance of SMART-3D is evaluated by extensive simulations in 2D and 3D environments populated with randomly moving dynamic obstacles. The results show that SMART-3D achieves high success rates and low replanning times, thus highlighting its suitability for real-time onboard applications.
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