A Hierarchical Framework for Coordinating Large-Scale Robot Networks
Refereed conference paper presented and published in conference proceedings


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AbstractIn 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.
All Author(s) ListZhe Liu, Shunbo Zhou, Hesheng Wang, Yi Shen, Haoang Li, Yun-Hui Liu
Name of Conference2019 International Conference on Robotics and Automation (ICRA)
Start Date of Conference20/05/2019
End Date of Conference24/05/2019
Place of ConferenceMontreal
Country/Region of ConferenceCanada
Proceedings Title2019 International Conference on Robotics and Automation (ICRA)
Detailed descriptionIn 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.
Year2019
PublisherIEEE
Pages6672 - 6677
ISBN978-1-5386-6026-3
LanguagesEnglish-United Kingdom
Keywordscollision avoidance, mobile robots, motion control, multi-robot systems, road traffic control, hierarchical framework, large-scale robot networks, motion coordination problems, multirobot system, robotic warehouses, automated transportation systems, life-long planning problem, coordination performance, robot motion uncertainties, hierarchical path planning, motion coordination structure, traffic heat-map, path planning level, sector-level path, path distance, motion coordination level, collision-free local path, rolling planning manner, traffic condition, robot uncertainty, Robot kinematics, Path planning, Task analysis, Collision avoidance, Planning, Topology

Last updated on 2021-11-01 at 23:36