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Mapping multiple gas/odor sources in an uncontrolled indoor environment using a Bayesian occupancy grid mapping based method
Authors
Alessio Mondini
Barbara Mazzolai
+34 more
Borenstein
Buhmann
Dana R. Yoerger
Farrell
Farrell
Ferri
Gabriele Ferri
Hayes
Ishida
Ishida
Ishida
Kazadi
Konolige
Kortenkamp
Lilienthal
Lilienthal
Lilienthal
Lilienthal
Lytridis
Marques
Michael V. Jakuba
Moravec
Murlis
Pang
Paolo Dario
Purnamadjaja
Pyk
Russell
Shraiman
Stachniss
Thrun
Thrun
Thrun
Virgilio Mattoli
Publication date
1 June 2011
Publisher
'Elsevier BV'
Doi
Cite
Abstract
Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Robotics and Autonomous Systems 59 (2011): 988–1000, doi:10.1016/j.robot.2011.06.007.In this paper we address the problem of autonomously localizing multiple gas/odor sources in an indoor environment without a strong airflow. To do this, a robot iteratively creates an occupancy grid map. The produced map shows the probability each discrete cell contains a source. Our approach is based on a recent adaptation [15] to traditional Bayesian occupancy grid mapping for chemical source localization problems. The approach is less sensitive, in the considered scenario, to the choice of the algorithm parameters. We present experimental results with a robot in an indoor uncontrolled corridor in the presence of different ejecting sources proving the method is able to build reliable maps quickly (5.5 minutes in a 6 m x 2.1 m area) and in real time
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