Machine learningMotion Planning
快速探索随机树
快速探索随机树（Rapidly-Exploring Random Tree, RRT）是一种运动规划算法，它通过迭代地在工作空间中采样随机构型并将其连接到树中最近的现有节点来构建可行路径的树。RRT 由 LaValle 于 1998 年提出，是高维运动规划的突破性进展，能够使机器人在具有障碍物、关节限制和运动学约束的复杂环境中找到无碰撞路径。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- LaValle, S. M. (1998). Rapidly-exploring random trees: A new tool for path planning. Technical Report TR 98-11, Iowa State University. link ↗
- Karaman, S., & Frazzoli, E. (2011). Sampling-based algorithms for optimal motion planning. International Journal of Robotics Research, 30(7), 846-894. DOI: 10.1177/0278364911406761 ↗
- LaValle, S. M. (2006). Planning Algorithms. Cambridge University Press. link ↗
如何引用本页
ScholarGate. (2026, June 3). Rapidly-Exploring Random Tree. ScholarGate. https://scholargate.app/zh/control-theory/rapidly-exploring-random-tree
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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