GaSLAM: An Algorithm for Simultaneous Gas Source Localization and Gas Distribution Mapping in 3D

Chemical gas dispersion poses considerable threat to humans, animals and the environment. The research areas of gas source localization and gas distribution mapping aim to localize the source of gas leaks and map the gas plume respectively, in order to help the coordination of swift rescue missions. Although very similar, these two areas are often treated separately in literature. In some cases, inferences on the gas distribution are made a posteriori from the source location, or vice-versa. In this paper, we introduce GaSLAM, a methodology that couples the estimation of the gas map and the source location using two state of the art algorithms with a novel navigation strategy based on informative quantities. The synergistic approach allows our algorithm to achieve a good estimation of both objectives and push the navigation strategies towards informative areas of the experimental volume. We validate the algorithm in simulation and with physical experiments in varying environmental conditions. We show that the algorithm improves on the source location estimate compared to a similar approach found in literature, and is able to deliver good quality maps of the gas distribution.