Safe Distributed Control of Multi-Robot Systems with Communication Delays

Fuente: arXiv
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Auteurs principaux: Ballotta, Luca, Talak, Rajat
Format: Preprint
Publié: 2024
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author Ballotta, Luca
Talak, Rajat
author_facet Ballotta, Luca
Talak, Rajat
contents Safe operation of multi-robot systems is critical, especially in communication-degraded environments such as underwater for seabed mapping, underground caves for navigation, and in extraterrestrial missions for assembly and construction. We address safety of networked autonomous systems where the information exchanged between robots incurs communication delays. We formalize a notion of distributed control barrier function for multi-robot systems, a safety certificate amenable to a distributed implementation, which provides formal ground to using graph neural networks to learn safe distributed controllers. Further, we observe that learning a distributed controller ignoring delays can severely degrade safety. We finally propose a predictor-based framework to train a safe distributed controller under communication delays, where the current state of nearby robots is predicted from received data and age-of-information. Numerical experiments on multi-robot collision avoidance show that our predictor-based approach can significantly improve the safety of a learned distributed controller under communication delays. A video abstract is available at https://youtu.be/Hcu1Ri32Spk.
format Preprint
id arxiv_https___arxiv_org_abs_2402_09382
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Safe Distributed Control of Multi-Robot Systems with Communication Delays
Ballotta, Luca
Talak, Rajat
Robotics
68T40 (Primary), 68M14, 68T07, 68W15 (Secondary)
C.2.4; I.2.6; I.2.9; I.2.11; J.2
Safe operation of multi-robot systems is critical, especially in communication-degraded environments such as underwater for seabed mapping, underground caves for navigation, and in extraterrestrial missions for assembly and construction. We address safety of networked autonomous systems where the information exchanged between robots incurs communication delays. We formalize a notion of distributed control barrier function for multi-robot systems, a safety certificate amenable to a distributed implementation, which provides formal ground to using graph neural networks to learn safe distributed controllers. Further, we observe that learning a distributed controller ignoring delays can severely degrade safety. We finally propose a predictor-based framework to train a safe distributed controller under communication delays, where the current state of nearby robots is predicted from received data and age-of-information. Numerical experiments on multi-robot collision avoidance show that our predictor-based approach can significantly improve the safety of a learned distributed controller under communication delays. A video abstract is available at https://youtu.be/Hcu1Ri32Spk.
title Safe Distributed Control of Multi-Robot Systems with Communication Delays
topic Robotics
68T40 (Primary), 68M14, 68T07, 68W15 (Secondary)
C.2.4; I.2.6; I.2.9; I.2.11; J.2
url https://arxiv.org/abs/2402.09382