ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time

被引:10
|
作者
Grothe, Francesco [1 ]
Hartmann, Valentin N. [1 ,2 ]
Orthey, Andreas [1 ]
Toussaint, Marc [1 ]
机构
[1] TU Berlin, Learning & Intelligent Syst Grp, Berlin, Germany
[2] Univ Stuttgart, Machine Learning & Robot Lab, Stuttgart, Germany
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2022) | 2022年
关键词
ALGORITHMS;
D O I
10.1109/ICRA46639.2022.9811814
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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).
引用
收藏
页码:3314 / 3320
页数:7
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