ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time
ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time
复制标题
ST-RRT*：时空渐近最优双向运动规划
DOI：
10.48550/arxiv.2203.02176
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Marc Toussaint
中科院分区：
文献类型：
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作者：
Francesco Grothe;Valentin N. Hartmann;A. Orthey;Marc Toussaint
我们提出了一个运动规划器规划通过动态障碍物，速度约束，和未知的到达时间的时空。我们的算法，时空RRT*（ST-RRT*），是一个概率完整的，双向的运动规划算法，这是渐近最优的最短到达时间。我们实验评估ST-RRT* 在两个抽象的（2D磁盘，8D磁盘在混乱的空间，并在一个狭窄的通道问题），和模拟机器人路径规划问题（顺序规划的8自由度移动的机器人，和7自由度机械臂）。所提出的规划优于RRT连接和RRT* 的初始解决方案的时间，并达到最终的解决方案的成本。ST-RRT* 的代码可在Open Motion Planning Library（OMPL）中找到。
We present a motion planner for planning through space-time with dynamic obstacles, velocity constraints, and unknown arrival time. Our algorithm, Space-Time RRT*(ST-RRT*), is a probabilistically complete, bidirectional motion planning algorithm, which is asymptotically optimal with respect to the shortest arrival time. We experimentally evaluate ST-RRT* in both abstract (2D disk, 8D disk in cluttered spaces, and on a narrow passage problem), and simulated robotic path planning problems (sequential planning of 8DoF mobile robots, and 7DoF robotic arms). The proposed planner outperforms RRT-Connect and RRT* on both initial solution time, and attained final solution cost. The code for ST-RRT* is available in the Open Motion Planning Library (OMPL).