By Topic

Manipulation planning of similar objects by part correspondence

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jacopo Aleotti ; RIMLab - Robotics and Intelligent Machines Laboratory, Dipartimento di Ingegneria dell'Informazione, University of Parma, Italy ; Stefano Caselli

Many innovative ideas in robotics have been inspired by neuroscience and, in particular, by the investigation of how intelligence and perception work. In this paper we explore an approach for semantic robot grasping, which combines programming by demonstration, automatic 3D shape segmentation and manipulation planning by parts. Neuro-psychology studies have evidenced the influence of shape decomposition for human perception of objects. In accordance to these findings a robot manipulation system is presented which is capable of learning and planning manipulation tasks for similar objects. The proposed approach allows a robot to perform intelligent grasping tasks by modeling the topology of an object. Manipulation tasks are demonstrated in virtual reality using a data glove. Results show that 3D shape segmentation enables both object retrieval and part-based grasping according to the affordances of an object.

Published in:

Advanced Robotics (ICAR), 2011 15th International Conference on

Date of Conference:

20-23 June 2011