  In this paper we propose a novel algorithm, Wi-Closure, to improve
computational efficiency and robustness of loop closure detection in
multi-robot SLAM. Our approach decreases the computational overhead of
classical approaches by pruning the search space of potential loop closures,
prior to evaluation by a typical multi-robot SLAM pipeline. Wi-Closure achieves
this by identifying candidates that are spatially close to each other by using
sensing over the wireless communication signal between robots, even when they
are operating in non-line-of-sight or in remote areas of the environment from
one another. We demonstrate the validity of our approach in simulation and
hardware experiments. Our results show that using Wi-closure greatly reduces
computation time, by 54% in simulation and by 77% in hardware compared, with a
multi-robot SLAM baseline. Importantly, this is achieved without sacrificing
accuracy. Using Wi-Closure reduces absolute trajectory estimation error by 99%
in simulation and 89.2% in hardware experiments. This improvement is due in
part to Wi-Closure's ability to avoid catastrophic optimization failure that
typically occurs with classical approaches in challenging repetitive
environments.
