From object categories to grasp transfer using probabilistic reasoning
2012 (English)In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE Computer Society, 2012, 1716-1723 p.Conference paper (Refereed)
In this paper we address the problem of grasp generation and grasp transfer between objects using categorical knowledge. The system is built upon an i) active scene segmentation module, able of generating object hypotheses and segmenting them from the background in real time, ii) object categorization system using integration of 2D and 3D cues, and iii) probabilistic grasp reasoning system. Individual object hypotheses are first generated, categorized and then used as the input to a grasp generation and transfer system that encodes task, object and action properties. The experimental evaluation compares individual 2D and 3D categorization approaches with the integrated system, and it demonstrates the usefulness of the categorization in task-based grasping and grasp transfer.
Place, publisher, year, edition, pages
IEEE Computer Society, 2012. 1716-1723 p.
, IEEE International Conference on Robotics and Automation, ISSN 2152-4092
Experimental evaluation, Individual objects, Integrated systems, Object categories, Object categorization, Probabilistic reasoning, Real time, Reasoning system, Scene segmentation, Task-based, Transfer systems, Robotics, Three dimensional
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-101528DOI: 10.1109/ICRA.2012.6225052ISI: 000309406701111ScopusID: 2-s2.0-84864441408ISBN: 978-146731403-9OAI: oai:DiVA.org:kth-101528DiVA: diva2:549673
2012 IEEE International Conference on Robotics and Automation, RiverCentre, Saint Paul, Minnesota, USA, May 14-18, 2012
FunderICT - The Next Generation
QC 201209052012-09-052012-08-302013-10-02Bibliographically approved