Abstract
This paper presents an active vision approach to enhance mobile robot localization. A particle filter localization is extended with a module to find active vision decisions that are optimal based on the current localization and its uncertainty. Optimality is expressed as a criterion of entropy minimization. Further approximations are introduced to enable real-time computation. Both the usefulness of the presented approach in a RoboCup scenario and the performance and quality of the approximations are evaluated in different static and dynamic situations.
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Czarnetzki, S., Kerner, S., Kruse, M. (2011). Real-Time Active Vision by Entropy Minimization Applied to Localization. In: Ruiz-del-Solar, J., Chown, E., Plöger, P.G. (eds) RoboCup 2010: Robot Soccer World Cup XIV. RoboCup 2010. Lecture Notes in Computer Science(), vol 6556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20217-9_23
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DOI: https://doi.org/10.1007/978-3-642-20217-9_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20216-2
Online ISBN: 978-3-642-20217-9
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