Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions

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Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions

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Cecchi, Michele / Paiano, Matteo / Mannucci, Anna / Palleschi, Alessandro / Pecora, Federico / Pallottino, Lucia

A standing challenge in current intralogistics is to reliably, effectively yet safely coordinate large-scale, heterogeneous multi-robot fleets without posing constraints on the infrastructure or unrealistic assumptions on robots. A centralized approach, proposed by some of the authors in prior work, allows to overcome these limitations with medium-scale fleets (i.e., tens of robots). With the aim of scaling to hundreds of robots, in this paper we explore a de-centralized variant of the same approach. The proposed framework maintains the key features of the original approach, namely, ensuring safety despite uncertainties on robot motions, and generality with respect to robot platforms, motion planners and controllers. We include considerations on liveness and solutions to prevent or recover from deadlocks in specific situations are reported and discussed. We validate the approach empirically with simulated, large, heterogeneous multi-robot fleets (up to 100 robots tested) operating both in benchmark and realistic environments. ; Funding Agencies: Ministry of Education, Universities and Research (MIUR) Semantic Robots KKS research ; H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) ; Semantic Robots KSS ; AutoHauler (Vinnova) ; CrossLab (Department of Excellence)

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Title :

Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions

Contributors:

Cecchi, Michele (author) / Paiano, Matteo (author) / Mannucci, Anna (author) / Palleschi, Alessandro (author) / Pecora, Federico (author) / Pallottino, Lucia (author)

Publication date :

2021-01-01

Remarks:

ISI:000670545200011

DOI :

https://doi.org/10.1109/LRA.2021.3091016

Type of media :

Article (Journal)

Type of material :

Electronic Resource

Language :

English