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

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Michele Cecchi, Matteo Paiano, Anna Mannucci, Alessandro Palleschi, Federico Pecora, Lucia Pallottino.
Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions. 
IEEE Robotics and Automation Letters, June 2021.

 

Abstract

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.

@ARTICLE{9461616,  
author={Cecchi, Michele and Paiano, Matteo and Mannucci, Anna and Palleschi, Alessandro and Pecora, Federico and Pallottino, Lucia},  
journal={IEEE Robotics and Automation Letters},
title={Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions},
year={2021},
volume={},
number={},
pages={1-1},
doi={10.1109/LRA.2021.3091016}}