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  Grasping with Vision Descriptors and Motor Primitives

Krömer, O., Detry, R., Piater, J., & Peters, J. (2011). Grasping with Vision Descriptors and Motor Primitives. In J. Andrade Cetto, J.-L. Ferrier, & J. Felipe (Eds.), Informatics in Control, Automation and Robotics: Revised and Selected Papers from the International Conference on Informatics in Control, Automation and Robotics 2010 (pp. 211-223). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0002-81E3-B Version Permalink: https://hdl.handle.net/21.11116/0000-0002-81E4-A
Genre: Conference Paper

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https://link.springer.com/content/pdf/10.1007%2F978-3-642-19539-6_14.pdf (Publisher version)
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 Creators:
Krömer, 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, ou_1497794              

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 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.

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 Dates: 2011
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-19539-6_14
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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

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Title: Informatics in Control, Automation and Robotics: Revised and Selected Papers from the International Conference on Informatics in Control, Automation and Robotics 2010
Source Genre: Proceedings
 Creator(s):
Andrade Cetto, J, Editor
Ferrier, J-L, Editor
Felipe, J, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 211 - 223 Identifier: ISBN: 978-3-642-19538-9

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Title: Lecture Notes in Electrical Engineering
Source Genre: Series
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Pages: - Volume / Issue: 89 Sequence Number: - Start / End Page: - Identifier: -