Robust dataglove mapping for recording human hand postures

Authors:
Jan Steffen;Jonathan Maycock;Helge Ritter
Affiliations:
Neuroinformatics Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany;Neuroinformatics Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany;Neuroinformatics Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany
Venue:
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
Year:
2011

Citing 1
Cited 1

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Abstract

We present a novel dataglove mapping technique based on parameterisable models that handle both the cross coupled sensors of the fingers and thumb, and the under-specified abduction sensors for the fingers. Our focus is on realistically reproducing the posture of the hand as a whole, rather than on accurate fingertip positions. The method proposed in this paper is a vision-free, object free, data glove mapping and calibration method that has been successfully used in robot manipulation tasks.