English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Grasping with Vision Descriptors and Motor Primitives

Kroemer, O., Detry, R., Piater, J., & Peters, J. (2010). Grasping with Vision Descriptors and Motor Primitives. In J. Filipe, J. Andrade-Cetto, & J.-L. Ferrier (Eds.), 7th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2010) (pp. 47-54). Lisboa, Portugal: SciTePress.

Item is

Files

show Files

Creators

show
hide
 Creators:
Kroemer, O1, 2, Author              
Detry, R, Author              
Piater, J, Author              
Peters, J1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: Grasping is one of the most important abilities needed for future service robots. Given the task of picking up an object from betweem clutter, traditional robotics approaches would determine a suitable grasping point and then use a movement planner to reach the goal. The planner would require precise and accurate information about the environment and long computation times, both of which may not always be available. Therefore, methods for executing grasps are required, which perform well with information gathered from only standard stereo vision, and make only a few necessary assumptions about the task environment. We propose techniques that reactively modify the robot’s learned motor primitives based on information derived from Early Cognitive Vision descriptors. The proposed techniques employ non-parametric potential fields centered on the Early Cognitive Vision descriptors to allow for curving hand trajectories around objects, and finger motions that adapt to the object’s local geometry. The methods were tested on a real robot and found to allow for easier imitation learning of human movements and give a considerable improvement to the robot’s performance in grasping tasks.

Details

show
hide
Language(s):
 Dates: 2010-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 6436
 Degree: -

Event

show
hide
Title: 7th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2010)
Place of Event: Funchal, Madeira, Portugal
Start-/End Date: 2010-06-15 - 2010-06-18

Legal Case

show

Project information

show

Source 1

show
hide
Title: 7th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2010)
Source Genre: Proceedings
 Creator(s):
Filipe, J, Editor
Andrade-Cetto, J, Editor
Ferrier, J-L, Editor
Affiliations:
-
Publ. Info: Lisboa, Portugal : SciTePress
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 47 - 54 Identifier: ISBN: 978-989-8425-01-0