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Master-slave hand system of different structures, grasp recognition by neural network and grasp mapping

Published online by Cambridge University Press:  26 November 2004

Tytus Wojtara
Affiliation:
Graduate School of Science and Technology, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba-shi 263-8522 (Japan).
Kenzo Nonami
Affiliation:
Department of Electronics and Mechanical Engineering, Chiba Univ., Yayoi-cho 1-33, Inage-ku, Chiba-shi 263-8522 (Japan).
Hui Shao
Affiliation:
Graduate School of Science and Technology, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba-shi 263-8522 (Japan).
Ryohei Yuasa
Affiliation:
Graduate School of Science and Technology, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba-shi 263-8522 (Japan).
Shingo Amano
Affiliation:
Department of Electronics and Mechanical Engineering, Chiba Univ., Yayoi-cho 1-33, Inage-ku, Chiba-shi 263-8522 (Japan).
Yasukazu Nobumoto
Affiliation:
Fuji Heavy Industries LTD., Oosawa 3-9-6, Mitaka-shi, Tokyo 181-8577 (Japan).

Abstract

This article is proposing a grasp recognition and grasp mapping method for a land mine clearance master-slave system. The system consists of a data glove and a powerful hydraulic hand. Because of the different structure of the master and slave hand a mapping from master grasp to slave grasp has to be implemented. The paper presents a grasp recognition method by Neural Network (NN) and a mapping method. The introduced mapping method allows the operator more intuitive grasping.

Type
Research Article
Copyright
2004 Cambridge University Press

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