WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot
Jens Kleesiek, Stephanie Badde, Stefan Wermter, Andreas K. Engel
2012
Abstract
We present a recurrent neural architecture with parametric bias for actively perceiving objects. A humanoid robot learns to extract sensorimotor laws and based on those to classify eight objects by exploring their multi-modal sensory characteristics. The network is either trained with prototype sequences for all objects or just two objects. In both cases the network is able to self-organize the parametric bias space into clusters representing individual objects and due to that, discriminates all eight categories with a very low error rate. We show that the network is able to retrieve stored sensory sequences with a high accuracy. Furthermore, trained with only two objects it is still able to generate fairly accurate sensory predictions for unseen objects. In addition, the approach proves to be very robust against noise.
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in Harvard Style
Kleesiek J., Badde S., Wermter S. and K. Engel A. (2012). WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot . In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-95-9, pages 64-73. DOI: 10.5220/0003729900640073
in Bibtex Style
@conference{icaart12,
author={Jens Kleesiek and Stephanie Badde and Stefan Wermter and Andreas K. Engel},
title={WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2012},
pages={64-73},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003729900640073},
isbn={978-989-8425-95-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot
SN - 978-989-8425-95-9
AU - Kleesiek J.
AU - Badde S.
AU - Wermter S.
AU - K. Engel A.
PY - 2012
SP - 64
EP - 73
DO - 10.5220/0003729900640073