Peter Stone's Selected Publications

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Action Selection for Illumination Invariant Color Learning

Mohan Sridharan and Peter Stone. Action Selection for Illumination Invariant Color Learning. In The IEEE International Conference on Intelligent Robots and Systems (IROS), 2007.

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Abstract

A major challenge in the path of widespread use of mobile robots is the ability to function autonomously, learning useful features from the environment and using them to adapt to environmental changes. We propose an algorithm for mobile robots equipped with color cameras that allows for smooth operation under illumination changes. The robot uses image statistics and the environmental structure to autonomously detect and adapt to both major and minor illumination changes. Furthermore, the robot autonomously plans an action sequence that maximizes color learning opportunities while minimizing localization errors. Our approach is fully implemented and tested on the Sony AIBO robots.

BibTeX Entry

@InProceedings{IROS07-mohan,
   author      = "Mohan Sridharan and Peter Stone",
   title       = "Action Selection for Illumination Invariant Color Learning",
   booktitle   = "The IEEE International Conference on Intelligent Robots and Systems (IROS)",
   year        = "2007",
   bibauthor   = "smohan",
   abstract = {A major challenge in the path of widespread use of
            mobile robots is the ability to function autonomously,
            learning useful features from the environment and using
            them to adapt to environmental changes. We propose an
            algorithm for mobile robots equipped with color cameras
            that allows for smooth operation under illumination
            changes. The robot uses image statistics and the
            environmental structure to autonomously detect and adapt
            to both major and minor illumination changes. Furthermore,
            the robot autonomously plans an action sequence that
            maximizes color learning opportunities while minimizing
            localization errors. Our approach is fully implemented and
            tested on the Sony AIBO robots.},
}

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