Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search
Abstract
This paper presents an effective multi-robot motion planner that enables each robot to reach its desired location while avoiding collisions with the other robots and the obstacles. The approach takes into account the differential constraints imposed by the underlying dynamics of each robot and generates dynamically-feasible motions that can be executed in the physical world. The crux of the approach is the sampling-based expansion of a motion tree in the continuous state space of all the robots guided by multi-agent search over a discrete abstraction. Experiments using vehicle models with nonlinear dynamics operating in complex environments show significant speedups over related work.
Cite
Text
Le and Plaku. "Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/744Markdown
[Le and Plaku. "Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/le2018ijcai-multi/) doi:10.24963/IJCAI.2018/744BibTeX
@inproceedings{le2018ijcai-multi,
title = {{Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search}},
author = {Le, Duong and Plaku, Erion},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {5314-5318},
doi = {10.24963/IJCAI.2018/744},
url = {https://mlanthology.org/ijcai/2018/le2018ijcai-multi/}
}