This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms: (1) coverage path planning using variable formations and (2) collaborative active sensing using multi-robot swarms. The state machine provides the logic for when to switch between these different sensing algorithms. We evaluate the performance of the proposed approach on a gas source localisation and mapping task. We use hardware-in-the-loop experiments and real-time experiments with a radio source simulating a real gas field. We compare the proposed approach with a single-mode, state-of-the-art collaborative active sensing approach. Our results indicate that our multi-modal switching approach can converge more rapidly than single-mode active sensing.
@article{arxiv.2306.04083,
title = {Coverage Path Planning with Budget Constraints for Multiple Unmanned Ground Vehicles},
author = {Vu Phi Tran and Asanka Perera and Matthew A. Garratt and Kathryn Kasmarik and Sreenatha Anavatti},
journal= {arXiv preprint arXiv:2306.04083},
year = {2023}
}