Abstract
This paper presents the methods used by team CSIRO Data61 for multi-agent coordination and exploration in the DARPA Subterranean (SubT) Challenge. The SubT competition involved a single operator sending teams of robots to rapidly explore underground environments with severe navigation and communication challenges. Coordination was framed as a multi-robot task allocation (MRTA) problem to allow for a seamless integration of exploration with other required tasks. Methods for extending a consensus-based task allocation approach for an online and highly dynamic mission are discussed. Exploration tasks were generated from frontiers in a map of traversable space, and graph-based heuristics applied to guide the selection of exploration tasks. Results from simulation, field testing, and the final competition are presented. Team CSIRO Data61 tied for most points scored and achieved second place during the final SubT event.
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This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA). The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.
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M.O. was the lead author. M.O., J.W. and R.A. contributed to the system design. M.O., J.W., S.C. and A.P. contributed to system implementation, experiment and analysis, and R.A. and N.K. provided guidance and oversight. The authors also thank Fletcher Talbot, Brendan Tidd, Brett Wood and Tom Hines for assistance with the field experiment.
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O’Brien, M., Williams, J., Chen, S. et al. Dynamic task allocation approaches for coordinated exploration of Subterranean environments. Auton Robot 47, 1559–1577 (2023). https://doi.org/10.1007/s10514-023-10142-4
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DOI: https://doi.org/10.1007/s10514-023-10142-4