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ICRA
2010
IEEE

Learning to grasp objects with multiple contact points

13 years 2 months ago
Learning to grasp objects with multiple contact points
— We consider the problem of grasping novel objects and its application to cleaning a desk. A recent successful approach applies machine learning to learn one grasp point in an image and a point cloud. Although those methods are able to generalize to novel objects, they yield suboptimal results because they rely on motion planner for finger placements. In this paper, we extend their method to accommodate grasps with multiple contacts. This approach works well for many humanmade objects because it models the way we grasp objects. To further improve the grasping, we also use a method that learns the ranking between candidates. The experiments show that our method is highly effective compared to a state-of-the-art competitor.
Quoc V. Le, David Kamm, A. F. Kara, Andrew Y. Ng
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICRA
Authors Quoc V. Le, David Kamm, A. F. Kara, Andrew Y. Ng
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