Probabilistic localization of gas emission areas with a mobile robot in indoor environments

Abstract

This work deals with the problem of gas source localization by a mobile robot with gas-sensing capabilities. Particularly, we address the problem for the case of indoor environments, where the presence of obstacles and the possibly complex structure with multiple rooms, inlets and outlets provoke the chaotic dispersion of the gases. Under these challenging conditions, where traditional approaches based on tracking or mathematical modeling of the plume cannot be applied, we propose a two-stage methodology to split the search into coarse and fine localization. Focusing on the broad localization, we contribute with a novel approach to estimate, from a set of sparse observations, the likelihood of different regions in the environment to hold a gas source. Experiments demonstrate that our approach is suitable to locate gas emission sources.