Learning grasping points with shape context
2010 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 0921-8830, Vol. 58, no 4, 362-377 p.Article in journal (Refereed) Published
This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.
Place, publisher, year, edition, pages
2010. Vol. 58, no 4, 362-377 p.
Grasping, Shape context, Affordances, SVM
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-28268DOI: 10.1016/j.robot.2009.10.003ISI: 000276666100003OAI: oai:DiVA.org:kth-28268DiVA: diva2:387474
FunderEU, FP7, Seventh Framework Programme, IST-FP7-IP GRASP (2008-2012)
QC 201101142011-01-142011-01-122012-01-20Bibliographically approved