Transferring human grasping synergies to a robot

被引：61

作者：

Geng, Tao ^{[1
]}

Lee, Mark ^{[1
]}

Huelse, Martin ^{[1
]}

机构：

[1] Aberystwyth Univ, Dept Comp Sci, Intelligent Robot Grp, Aberystwyth, Dyfed, Wales

来源：

MECHATRONICS | 2011年 / 21卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

Human-robot skill transfer; Synergy; Robotic grasping; SKILLS;

D O I：

10.1016/j.mechatronics.2010.11.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a system for transferring human grasping skills to a robot is presented. In order to reduce the dimensionality of the grasp postures, we extracted three synergies from data on human grasping experiments and trained a neural network with the features of the objects and the coefficients of the synergies. Then, the trained neural network was employed to control robot grasping via an individually optimized mapping between the human hand and the robot hand. As force control was unavailable on our robot hand, we designed a simple strategy for the robot to grasp and hold the objects by exploiting tactile feedback at the fingers. Experimental results demonstrated that the system can generalize the transferred skills to grasp new objects. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：272 / 284

页数：13

共 27 条

[1]

[Anonymous], P IEEE RAS INT C HUM

[2]

[Anonymous], P INT C DEV LEARN

[3]

Bicchi A., 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), P348, DOI 10.1109/ROBOT.2000.844081

[4]

BROWN CY, 2007, THESIS MIT

[5]

Chen PCY, 1996, MACH LEARN, V23, P191, DOI 10.1007/BF00117444

[6]

Chow Yang-Wai., 2009, International Journal of Recent Trends in Engineering, V1, P52

[7] Sensor fusion for human-robot skill transfer systems [J].

Cortesao, R ;

Koeppe, R .

ADVANCED ROBOTICS, 2000, 14 (06) :537-549

[8] Shared and specific muscle synergies in natural motor behaviors [J].

d'Avella, A ;

Bizzi, E .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2005, 102 (08) :3076-3081

[9] Running over rough terrain: guinea fowl maintain dynamic stability despite a large unexpected change in substrate height [J].

Daley, MA ;

Usherwood, JR ;

Felix, G ;

Biewener, AA .

JOURNAL OF EXPERIMENTAL BIOLOGY, 2006, 209 (01) :171-187

[10] Goal-directed imitation for robots: A bio-inspired approach to action understanding and skill learning [J].

Erlhagen, W. ;

Mukovskiy, A. ;

Bicho, E. ;

Panin, G. ;

Kiss, C. ;

Knoll, A. ;

van Schie, H. ;

Bekkering, H. .

ROBOTICS AND AUTONOMOUS SYSTEMS, 2006, 54 (05) :353-360

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