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Experimental Analysis of Gas-Sensitive Braitenberg Vehicles
Experimental Analysis of
Gas-Sensitive Braitenberg Vehicles
Achim Lilienthal1 and Tom Duckett2
1 W.-Schickard-Inst. for Comp. Science, University of Tu?bingen, Sand 1, 72074 Tu?bingen, Germany
2 Department of Technology, AASS, O?rebro University, S-70182 O?rebro, Sweden
Abstract. This article addresses the problem of localising a static gas source in an indoor environ-
ment by a mobile robot. In contrast to previous works, the environment is not artificially ventilated
to produce a strong unidirectional airflow. Here, the dominant transport mechanisms of gas molecules
are turbulence and convection flow rather than diffusion, which results in a patchy, chaotically fluctu-
ating gas distribution. Two Braitenberg-type strategies (positive and negative tropotaxis) based on
the instantaneously measured spatial concentration gradient were investigated. Both strategies were
shown to be of potential use for gas source localisation. As a possible solution to the problem of gas
source declaration (the task of determining with certainty that the gas source has been found), an
indirect localisation strategy based on exploration and concentration peak avoidance is suggested.
Here, a gas source is located by exploiting the fact that local concentration maxima occur more
frequently near the gas source compared to distant regions.
1 Introduction
Using electrochemical sensors on a mobile robot is very promising for a broad range of
applications. A robot equipped with gas sensors could be utilised as an electronic watchman
that is able to detect, localise and identify odours, perhaps indicating toxic gas leaks,
leaking solvents or a fire at its initial stage. Furthermore self-produced odours can be
used to aid navigation [5] or to communicate with other robots, for instance by sending a
chemical SOS signal [30].
Localising a gas source in real world environments is a challenging task mainly because
the distribution of odourant molecules is usually dominated by turbulence rather than
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