Real-time active vision by entropy minimization applied to localization

Authors:
Stefan Czarnetzki;Sören Kerner;Michael Kruse
Affiliations:
Robotics Research Institute, Section Information Technology, TU Dortmund University, Dortmund, Germany;Robotics Research Institute, Section Information Technology, TU Dortmund University, Dortmund, Germany;Robotics Research Institute, Section Information Technology, TU Dortmund University, Dortmund, Germany
Venue:
RoboCup 2010
Year:
2011

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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.