期刊
ROBOTICS AND AUTONOMOUS SYSTEMS
卷 58, 期 4, 页码 362-377出版社
ELSEVIER
DOI: 10.1016/j.robot.2009.10.003
关键词
Grasping; Shape context; Affordances; SVM
资金
- EU
This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects. (C) 2009 Elsevier B.V. All rights reserved.
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