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

Autor: Alessandro Palleschi, Matteo Paiano, Federico Pecora, Michele Cecchi, Anna Mannucci, Lucia Pallottino
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Publikationer från Örebro universitet.
Popis: 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)
Databáze: OpenAIRE