Entropy-based active vision for a humanoid soccer robot

Authors:
Andreas Seekircher;Tim Laue;Thomas Röfer
Affiliations:
University of Miami, Department of Computer Science, Coral Gables, FL;Deutsches Forschungszentrum für Künstliche Intelligenz, Sichere Kognitive Systeme, Bremen, Germany;Deutsches Forschungszentrum für Künstliche Intelligenz, Sichere Kognitive Systeme, Bremen, Germany
Venue:
RoboCup 2010
Year:
2011

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Abstract

In this paper, we show how the estimation of a robot's world model can be improved by actively sensing the environment through considering the current world state estimate through minimizing the entropy of an underlying particle distribution. Being originally computationally expensive, this approach is optimized to become executable in real-time on a robot with limited resources. We demonstrate the approach on a humanoid robot, performing self-localization and ball tracking on a RoboCup soccer field.