Arrow Research search
Back to AAMAS

AAMAS 2022

Context-Aware Modelling for Multi-Robot Systems Under Uncertainty

Conference Paper Main Track Autonomous Agents and Multiagent Systems

Abstract

Formal models of multi-robot behaviour are fundamental to planning, simulation, and model checking techniques. However, existing models are invalidated by strong assumptions that fail to capture execution-time multi-robot behaviour, such as simplistic duration models or synchronisation constraints. In this paper we propose a novel multi-robot Markov automaton formulation which models asynchronous multi-robot execution in continuous time. Robot dynamics are captured using phase-type distributions over action durations. Moreover, we explicitly model the effects of robot interactions, as they are a key factor for the duration of action execution. We also present a scalable discrete-event simulator which yields realistic statistics over execution-time robot behaviour by sampling through the Markov automaton. We validate our model and simulator against a Gazebo simulation in a range of multi-robot navigation scenarios, demonstrating that our model accurately captures highlevel multi-robot behaviour.

Authors

Keywords

  • Multi-robot systems
  • Markov automata
  • Discrete-event simulation

Context

Venue
International Conference on Autonomous Agents and Multiagent Systems
Archive span
2002-2026
Indexed papers
8043
Paper id
507183686399736803
v2026.09.13