Dimensionality reduction for hand-independent dexterous robotic grasping

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 redu...

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Bibliographic Details
Published in2007 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 3270 - 3275
Main Authors Ciocarlie, M., Goldfeder, C., Allen, P.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.10.2007
Subjects
Algorithm design and analysis
Automatic control
Data gloves
Grasping
Humans
Intelligent robots
Neuroscience
Orbital robotics
Taxonomy
Testing
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Summary: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.
ISBN:9781424409112
142440911X
ISSN:2153-0858
DOI:10.1109/IROS.2007.4399227