Dimensionality reduction for hand-independent dexterous robotic grasping

Ciocarlie, Matei; Goldfeder, Corey; Allen, Peter K.

In this paper, we build upon recent advances in neuroscience research which have shown that control of the human hand during grasping is dominated by movement in a configuration space of highly reduced dimensionality. We extend this concept to robotic hands and show how a similar dimensionality reduction can be defined for a number of different hand models. This framework can be used to derive planning algorithms that produce stable grasps even for highly complex hand designs. Furthermore, it offers a unified approach for controlling different hands, even if the kinematic structures of the models are significantly different. We illustrate these concepts by building a comprehensive grasp planner that can be used on a large variety of robotic hands under various constraints.



Also Published In

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems: San Diego, CA, 29 October - 2 November 2007

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Academic Units
Computer Science
Published Here
November 2, 2012