Adaptive 3-D Object Classification with Reinforcement Learning

Jens Garstka; Gabriele Peters

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Paper

Adaptive 3-D Object Classification with Reinforcement Learning

Topics: Vision, Recognition and Reconstruction

In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, 381-385, 2015 , Colmar, Alsace, France

Authors: Jens Garstka and Gabriele Peters

Affiliation: University of Hagen, Germany

Keyword(s): 3-D Object Classification, Reinforcement Learning.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Robotics and Automation ; Vision, Recognition and Reconstruction

Abstract: We propose an adaptive approach to 3-D object classification. In this approach appropriate 3-D feature descriptor algorithms for 3-D point clouds are selected via reinforcement learning depending on properties of the objects to be classified. This approach is supposed to be able to learn strategies for an advantageous selection of 3-D point cloud descriptor algorithms in an autonomous and adaptive way, and thus is supposed to yield higher object classification rates in unfamiliar environments than any of the single algorithms alone. In addition, we expect our approach to be able to adapt to subsequently added 3-D feature descriptor algorithms as well as to autonomously learn new object categories when encountered in the environment without further user assistance. We describe the 3-D object classification pipeline based on local 3-D features and its integration into the reinforcement learning environment.

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Paper citation in several formats:

Garstka, J. and Peters, G. (2015). Adaptive 3-D Object Classification with Reinforcement Learning. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-123-6; ISSN 2184-2809, SciTePress, pages 381-385. DOI: 10.5220/0005563803810385

@conference{icinco15,
author={Jens Garstka. and Gabriele Peters.},
title={Adaptive 3-D Object Classification with Reinforcement Learning},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2015},
pages={381-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005563803810385},
isbn={978-989-758-123-6},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Adaptive 3-D Object Classification with Reinforcement Learning
SN - 978-989-758-123-6
IS - 2184-2809
AU - Garstka, J.
AU - Peters, G.
PY - 2015
SP - 381
EP - 385
DO - 10.5220/0005563803810385
PB - SciTePress