Exploration and localization of a gas source with MOX gas sensors on a mobile robot — A Gaussian regression bout amplitude approach

Abstract

Mobile robot olfaction systems combine gas sensors with mobility provided by robots. They relief humans of dull, dirty and dangerous tasks in applications such as search & rescue or environmental monitoring. We address gas source localization and especially the problem of minimizing exploration time of the robot, which is a key issue due to energy constraints. We propose an active search approach for robots equipped with MOX gas sensors and an anemometer, given an occupancy map. Events of rapid change in the MOX sensor signal (“bouts”) are used to estimate the distance to a gas source. The wind direction guides a Gaussian regression, which interpolates distance estimates. The contributions of this paper are two-fold. First, we extend previous work on gas source distance estimation with MOX sensors and propose a modification to cope better with turbulent conditions. Second, we introduce a novel active search gas source localization algorithm and validate it in a real-world environment.