Hierarchical Model Predictive Control for Multi-Robot Navigation
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3140-3145.
Abstract
Ensuring the stability is the most important requirement for the navigation control of multi-robot systems with no reference trajectory. The popular heuristic-search methods cannot provide theoretical guarantees on stability. In this paper, we propose a Hierarchical Model Predictive Control scheme that employs reachable sets to decouple the navigation problem of linear dynamical multi-robot systems. The proposed control scheme guarantees the stability and feasibility, and is more efficient and viable than other Model Predictive Control schemes, as evidenced by our simulation results.
@inproceedings{ijcai2016p445,
title = {Hierarchical Model Predictive Control for Multi-Robot Navigation},
author = {Huang, Chao and Chen, Xin and Zhang, Yifan and Qin, Shengchao and Zeng, Yifeng and Li, Xuandong},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {3140--3145},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/445},
}
TY - CPAPER TI - Hierarchical Model Predictive Control for Multi-Robot Navigation AU - Huang, Chao AU - Chen, Xin AU - Zhang, Yifan AU - Qin, Shengchao AU - Zeng, Yifeng AU - Li, Xuandong T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 3140 EP - 3145 UR - https://ijcai.org/proceedings/2016/445 ER -Copied
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