A Hierarchical Framework for Coordinating Large-Scale Robot Networks
Zhe Liu, Shunbo Zhou, Hesheng Wang, Yi Shen, Haoang Li, Yun-Hui Liu
Abstract
In this paper, we study the cooperative path planning and motion coordination problems of the multi-robot system with large number of robots, aiming for practical applications in robotic warehouses and automated transportation systems. Particularly, we solve the life-long planning problem and guarantee the coordination performance in the presence of robot motion uncertainties. A hierarchical path planning and motion coordination structure is presented. The environment is divided into several sectors and a traffic heat-map is presented to describe the current sector-level traffic condition. In path planning level, the sector-level path is calculated by considering the path distance, the current traffic condition and the current robot uncertainty. In motion coordination level, local cooperative A* algorithm and conflict-based searching strategy are utilized within each sector to generate the collision-free local path of each robot in a rolling planning manner. The effectiveness and practical applicability of the proposed approach are validated by simulations with more than one thousand robots and real experiments.
BibTeX
@inproceedings{icra2019_ahierarchicalfra,
title = {A Hierarchical Framework for Coordinating Large-Scale Robot Networks},
author = {Zhe Liu and Shunbo Zhou and Hesheng Wang and Yi Shen and Haoang Li and Yun-Hui Liu},
booktitle = {ICRA 2019},
year = {2019}
}