Interactive object classification using sensorimotor contingencies
2013 (English)In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE , 2013, 2799-2805 p.Conference paper (Refereed)
Understanding and representing objects and their function is a challenging task. Objects we manipulate in our daily activities can be described and categorized in various ways according to their properties or affordances, depending also on our perception of those. In this work, we are interested in representing the knowledge acquired through interaction with objects, describing these in terms of action-effect relations, i.e. sensorimotor contingencies, rather than static shape or appearance representations. We demonstrate how a robot learns sensorimotor contingencies through pushing using a probabilistic model. We show how functional categories can be discovered and how entropy-based action selection can improve object classification.
Place, publisher, year, edition, pages
IEEE , 2013. 2799-2805 p.
, IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Action selection, Affordances, Daily activity, Entropy-based, Interactive objects, Object classification, Probabilistic modeling, Sensorimotor contingencies
IdentifiersURN: urn:nbn:se:kth:diva-134623DOI: 10.1109/IROS.2013.6696752ISI: 000331367402139ScopusID: 2-s2.0-84891028676ISBN: 978-1-4673-6358-7OAI: oai:DiVA.org:kth-134623DiVA: diva2:667351
2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013; Tokyo; Japan; 3 November 2013 through 8 November 2013
FunderEU, FP7, Seventh Framework Programme, FP7-IST-270212
QC 201312172013-11-262013-11-262014-04-10Bibliographically approved