Identification of a Human Hand Kinematics by Measuring and Merging of Nail-Based Finger Motions
Hidenori Tani, Ryo Nozawa, Tomomichi Sugihara
Abstract
A method to identify the kinematics model of a human hand that less suffers from the skin artifact is proposed based on a fact that the movements of nails with respect to the corresponding fingertip bones are much smaller than that of skin. It consists of two stages. In the first (individual) stage, the most likely combination of joint assignments and angles of each finger is identified through a dual-phase least squares method (LSM), where the joint angles are estimated in the inner LSM and the joint assignments in the outer LSM, from the movement of the hand dorsum with respect to the base coordinate frame attached to each nail. In the second (merging) stage, kinematic models of each finger are merged so as to compromise the estimated movements of the hand dorsum by them also through the dual-phase LSM. It is shown that the identified joint assignments have an advantage over several existing anthropomorphic robot hands based on the distribution of pinchability (DOP), which is also proposed in this paper as a novel index to evaluate the ability of in-hand manipulation.
BibTeX
@inproceedings{iros2020_identificationof,
title = {Identification of a Human Hand Kinematics by Measuring and Merging of Nail-Based Finger Motions},
author = {Hidenori Tani and Ryo Nozawa and Tomomichi Sugihara},
booktitle = {IROS 2020},
year = {2020}
}