A Hybrid Approach For Grasping 3D Objects

被引：19
|
作者：
Sahbani, Anis [1 ]
El-Khoury, Sahar [2 ]
机构：
[1] Univ Paris 06, ISIR CNRS, UMR 7222, F-75005 Paris, France
[2] Univ Paris 06, L2E, F-75005 Paris, France
来源：
2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS | 2009年
关键词：
D O I：
10.1109/IROS.2009.5354105
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper presents a novel strategy that learns to associate a grasp to an unknown object/task. A hybrid approach combining empirical and analytical methods is proposed. The empirical step ensures task-compatibility by learning to identify the object graspable part in accordance with humans choice. The analytical step permits contact points generation guaranteeing the grasp stability. The robotic hand kinematics are also taken into account. The corresponding results are illustrated using Grasp It interface [1].
引用
收藏
页码：1272 / 1277
页数：6
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