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Learning how to grasp objects

Baldassarre, L; Barla, A; Noceti, N; Odone, F; (2010) Learning how to grasp objects. In: Verleysen, M, (ed.) ESANN 2010 proceedings: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges (Belgium), 28-30 April 2010. (pp. 289 - 294). d-side: Evere, Belgium. Green open access

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Abstract

This paper deals with the problem of estimating an appropriate hand posture to grasp an object, from 2D object’s visual cues in a many-to-many (objects,grasp) configuration. A statistical learning protocol implementing vector-valued regression is adopted for both classifying the most likely grasp type and estimating the hand posture. An extensive experimental evaluation on a publicly available dataset of visuo-motor data reports very promising results and encourages further investigations.

Type:Proceedings paper
Title:Learning how to grasp objects
ISBN:2930307102
Open access status:An open access version is available from UCL Discovery
Publisher version:http://www.dice.ucl.ac.be/esann/proceedings/papers.php?ann=2010
Additional information:owner: baldassarre timestamp: 2010.01.21 Copyright information from European Symposium on Artificial Neural Networks Electronic Proceedings home page at http://www.dice.ucl.ac.be/esann/proceedings/electronicproceedings.htm : You are free to download, copy and distribute any paper contained in these pages, provided that you keep the reference of the paper that has been added as header to each page.
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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