Collecting a Database for Studying Gas Distribution Mapping and Gas Source Localization with Mobile Robots

Abstract

In this paper, we present our initial experiments to collect a database for studying mobile robot olfaction. Mobile robots with olfactory sensing capabilities are expected to be used in various applications including gas distribution mapping and gas source localization. Owing to the turbulent nature of the airflow field and the gas distribution, these robots must be equipped with algorithms that can cope with chaotic environments. Since it is important to check the applicability of such algorithms in a diversity of environments, we propose to build a database with which the users can test the performances of their own algorithms in various environments. The database collected so far consists of two parts: a basic data set collected in a well-characterized controlled indoor environment and applied data sets collected in uncontrolled indoor and outdoor environments. A result of applying the database for testing a gas-source localization algorithm are shown as an example. We believe that such database will accelerate the research advancements on mobile robot olfaction.