  Gas source localization (GSL) with an autonomous robot is a problem with many
prospective applications, from finding pipe leaks to emergency-response
scenarios. In this work, we present a new method to perform GSL in realistic
indoor environments, featuring obstacles and turbulent flow. Given the highly
complex relationship between the source position and the measurements available
to the robot (the single-point gas concentration, and the wind vector) we
propose an observation model that derives from contrasting the online,
real-time simulation of the gas dispersion from any candidate source
localization against a gas concentration map built from sensor readings. To
account for a convenient and grounded integration of both into a probabilistic
estimation framework, we introduce the concept of probabilistic gas-hit maps,
which provide a higher level of abstraction to model the time-dependent nature
of gas dispersion. Results from both simulated and real experiments show the
capabilities of our current proposal to deal with source localization in
complex indoor environments.
