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Conference Papers Year : 2022

Multi-robot persistent environmental monitoring based on constraint-driven execution of learned robot tasks

Abstract

This paper considers a multi-robot team tasked with monitoring an environmental field of interest over long time horizons. The approach is based on a control-theoretic measure of the information collected by the robots, namely a norm of the constructability Gramian. This measure is leveraged in order to learn a distributed multi-robot control policy using the reinforcement learning paradigm. The learned policy is then combined with energy constraints using the constraint-driven control framework in order to achieve persistent environmental monitoring. The proposed approach is tested in a simulated multi-robot persistent environmental monitoring scenario where a team of robots with limited availability of energy is to be controlled in a coordinated fashion in order to estimate the concentration of a gas diffusing in the environment.
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Dates and versions

hal-03594774 , version 1 (02-03-2022)

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Gennaro Notomista, Claudio Pacchierotti, Paolo Robuffo Giordano. Multi-robot persistent environmental monitoring based on constraint-driven execution of learned robot tasks. ICRA 2022 - IEEE International Conference on Robotics and Automation, May 2022, Philadelphia, United States. pp.6853-6859, ⟨10.1109/ICRA46639.2022.9811673⟩. ⟨hal-03594774⟩
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