Interactive Perception Based on Gaussian Process Classification for House-Hold Objects Recognition and Sorting

Khan, A., Sun, L., Aragon-Camarasa, G. and Siebert, J. P. (2017) Interactive Perception Based on Gaussian Process Classification for House-Hold Objects Recognition and Sorting. In: IEEE International Conference on Robotics and Biomimetics, Qingdao, China, 03-07 Dec 2016, pp. 1087-1092. ISBN 9781509043644 (doi: 10.1109/ROBIO.2016.7866470)

Abstract

We present an interactive perception model for object sorting based on Gaussian Process (GP) classification that is capable of recognizing objects categories from point cloud data. In our approach, FPFH features are extracted from point clouds to describe the local 3D shape of objects and a Bag-of-Words coding method is used to obtain an object-level vocabulary representation. Multi-class Gaussian Process classification is employed to provide and probable estimation of the identity of the object and serves a key role in the interactive perception cycle – modelling perception confidence. We show results from simulated input data on both SVM and GP based multi-class classifiers to validate the recognition accuracy of our proposed perception model. Our results demonstrate that by using a GP-based classifier, we obtain true positive classification rates of up to 80%. Our semi-autonomous object sorting experiments show that the proposed GP based interactive sorting approach outperforms random sorting by up to 30% when applied to scenes comprising configurations of household objects.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Khan, Dr Aamir and Sun, Mr Li and Siebert, Dr Paul and Aragon Camarasa, Dr Gerardo
• Authors: Khan, A., Sun, L., Aragon-Camarasa, G., and Siebert, J. P.
• College/School: College of Science and Engineering > School of Chemistry; College of Science and Engineering > School of Computing Science
• ISBN: 9781509043644
• Copyright Holders: Copyright © 2016 IEEE
• First Published: First published in IEEE International Conference on Robotics and Biomimetics 2016
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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