Interactive grasp learning based on human demonstration
2004 (English)In: 2004 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1- 5, PROCEEDINGS, 2004, 3519-3524 p.Conference paper (Refereed)
We describe our effort in development of an artificial cognitive system, able of performing complex manipulation tasks in a teleoperated or collaborative manner. Some of the work is motivated by human control strategies that, in general, involve comparison between sensory feedback and a-priori known, internal models. According to recent neuroscientific findings, predictions help to reduce the delays in obtaining the sensory information and to perform more complex tasks. This paper deals with the issue of robotic manipulation and grasping in particular. Two main contributions of the paper are: i) evaluation, recognition and modeling of human grasps during the arm transportation sequence, and ii) learning and representation of grasp strategies for different robotic hands.
Place, publisher, year, edition, pages
2004. 3519-3524 p.
, IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ISSN 1050-4729
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-44355DOI: 10.1109/ROBOT.2004.1308798ISI: 000221794800566ScopusID: 2-s2.0-3042693081ISBN: 0-7803-8232-3OAI: oai:DiVA.org:kth-44355DiVA: diva2:450905
IEEE International Conference on Robotics and Automation Location: New Orleans, LA Date: APR 26-MAY 01, 2004
QC 201110242011-10-242011-10-202012-01-24Bibliographically approved