A Kendama learning robot based on bi-directional theory

被引:91
作者
Miyamoto, H
Schaal, S
Gandolfo, F
Gomi, H
Koike, Y
Osu, R
Nakano, E
Wada, Y
Kawato, M
机构
[1] ATR HUMAN INFORMAT PROC RES LABS, KYOTO, JAPAN
[2] GEORGIA INST TECHNOL, ATLANTA, GA 30332 USA
[3] MIT, CAMBRIDGE, MA 02139 USA
[4] NIPPON TELEGRAPH & TEL PUBL CORP, BASIC RES LABS, KANAGAWA, JAPAN
[5] TOYOTA MOTOR CO LTD, TOYOTA, JAPAN
[6] KYOTO UNIV, KYOTO 606, JAPAN
[7] KOBE UNIV, KOBE 657, JAPAN
[8] KAWASAKI STEEL CHEM IND CO LTD, KAWASAKI, KANAGAWA, JAPAN
关键词
teaching by showing; task-level learning; dynamic optimization;
D O I
10.1016/S0893-6080(96)00043-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A general theory of movement-pattern perception based on bi-directional theory for sensory-motor integration can be used for motion capture and learning by watching in robotics. We demonstrate our methods using the game of Kendama, executed by the SARCOS Dextrous Slave Arm, which has a very similar kinematic structure to the human arm. Three ingredients have to be integrated for the successful execution of this task. The ingredients are (1) to extract via-points from a human movement trajectory using a forward-inverse relaxation model, (2) to treat via-points as a control variable while reconstructing the desired trajectory from all the via-points, and (3) to modify the via-points for successful execution. In order to test the validity of the via-point representation, we utilized a numerical model of the SARCOS arm, and examined the behavior of the system under several conditions. Copyright (C) 1996 Elsevier Science Ltd.
引用
收藏
页码:1281 / 1302
页数:22
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