COMPARISON OF CLASSICAL AND INTERACTIVE MULTI-ROBOT EXPLORATION STRATEGIES IN POPULATED ENVIRONMENTS

Nassim Kalde, Olivier Simonin, François Charpillet

Abstract


Multi-robot exploration consists in coordinating robots for mapping an unknown environment. It raises several issues concerning task allocation, robot control, path planning and communication. We study exploration in populated environments, in which pedestrian flows can severely impact performances. However, humans have adaptive skills for taking advantage of these flows while moving. Therefore, in order to exploit these human abilities, we propose a novel exploration strategy that explicitly allows for human-robot interactions. Our model for exploration in populated environments combines the classical frontier-based strategy with our interactive approach. We implement interactions where robots can locally choose a human guide to follow and define a parametric heuristic to balance interaction and frontier assignments. Finally, we evaluate to which extent human presence impacts our exploration model in terms of coverage ratio, travelled distance and elapsed time to completion.

Keywords


artificial intelligence; multi-agent system; robotic exploration; human-robot interaction

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN 1210-2709 (Print)
ISSN 1805-2363 (Online)
Published by the Czech Technical University in Prague