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Online Unsupervised Cumulative Learning For Life-Long Robot Operation

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Gatsoulis, Y, Burbridge, C and McGinnity, TM (2011) Online Unsupervised Cumulative Learning For Life-Long Robot Operation. In: 2011 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO'2011, Phuket, Thailand. IEEE. 6 pp. [Conference contribution]

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Abstract

The effective life-long operation of service robots and assistive companions depends on the robust ability of the system to learn cumulatively and in an unsupervised manner. For a cumulative learning robot there are particular characteristics that the system should have, such as being able to detect new perceptions, being able to learn online and without supervision, expand when required, etc. Bag-of-Words is a generic and compact representation of visual perceptions which has commonly and successfully been used in object recognition problems. However in its original form, it is unable to operate online and expand its vocabulary when required.This paper describes a novel method for cumulative unsupervised learning of objects by visual inspection, using an online and expanding when required Bag-of-Words. We present a set of experiments with a real-world robot, which cumulatively learns a series of objects. The results show that the system is able to learn cumulatively and recall correctly the objects it was trained on.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:20646
Deposited By:Dr Ioannis Gatsoulis
Deposited On:17 Jan 2012 15:10
Last Modified:17 Jan 2012 15:10

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