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Learning how to grasp objects
Year: 2010 Keywords: Grasp action classification, vector-valued regression
Authors: Annalisa Barla, Baldassarre Luca, Nicoletta Noceti, Francesca Odone  
Book title: Proc. of ESANN, European Symposium on Artificial Neural Networks
Pages: 1-6
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.
Digital version