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A statistical approach to gas distribution modelling with mobile robots - The Kernel DM+V algorithm

8 years 10 months ago
A statistical approach to gas distribution modelling with mobile robots - The Kernel DM+V algorithm
— Gas distribution modelling constitutes an ideal application area for mobile robots, which – as intelligent mobile gas sensors – offer several advantages compared to stationary sensor networks. In this paper we propose the Kernel DM+V algorithm to learn a statistical 2-d gas distribution model from a sequence of localized gas sensor measurements. The algorithm does not make strong assumptions about the sensing locations and can thus be applied on a mobile robot that is not primarily used for gas distribution monitoring, and also in the case of stationary measurements. Kernel DM+V treats distribution modelling as a density estimation problem. In contrast to most previous approaches, it models the variance in addition to the distribution mean. Estimating the predictive variance entails a significant improvement for gas distribution modelling since it allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluat...
Achim J. Lilienthal, Matteo Reggente, Marco Trinca
Added 24 May 2010
Updated 24 May 2010
Type Conference
Year 2009
Where IROS
Authors Achim J. Lilienthal, Matteo Reggente, Marco Trincavelli, Jose-Luis Blanco, Javier Gonzalez
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