Learning Grasping Affordance Using Probabilistic and Ontological Approaches
2009 (English)In: 2009 International Conference on Advanced Robotics, ICAR 2009, IEEE , 2009, 96-101 p.Conference paper (Refereed)
We present two approaches to modeling affordance relations between objects, actions and effects. The first approach we present focuses on a probabilistic approach which uses a voting function to learn which objects afford which types of grasps. We compare the success rate of this approach to a second approach which uses an ontological reasoning engine for learning affordances. Our second approach employs a rule-based system with axioms to reason on grasp selection for a given object.
Place, publisher, year, edition, pages
IEEE , 2009. 96-101 p.
Affordances, Ontological approach, Ontological reasoning, Probabilistic approaches, Rule based system, Ontology
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-30419ISI: 000270815500016ScopusID: 2-s2.0-70449371324ISBN: 978-1-4244-4855-5OAI: oai:DiVA.org:kth-30419DiVA: diva2:400824
2009 International Conference on Advanced Robotics, ICAR 2009; Munich; Germany; 22 June 2009 through 26 June 2009
QC 201102282011-02-282011-02-242014-10-09Bibliographically approved