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JRM Vol.18 No.1 pp. 44-50
doi: 10.20965/jrm.2006.p0044
(2006)

Paper:

A Stable Approach for Modular Learning and its Application to Autonomous Aero-Robot

Mai Bando, and Hiroaki Nakanishi

Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto 606-8501, Japan

Received:
May 10, 2005
Accepted:
September 26, 2005
Published:
February 20, 2006
Keywords:
modular learning, reinforcement learning, designing control system, autonomous robot
Abstract

A control system for an autonomous robot, which consists of several cooperative modules whose combination and structures change dynamically through interaction with environment, is discussed in this paper. We propose a method to design a control system by modular learning based on Lyapunov design method. In our method, modules that have different property and the dynamic relations between modules to achieve the task are learned. Numerical simulations and flight experiment of an autonomous aero-robot demonstrate the effectiveness of the proposed method.

Cite this article as:
Mai Bando and Hiroaki Nakanishi, “A Stable Approach for Modular Learning and its Application to Autonomous Aero-Robot,” J. Robot. Mechatron., Vol.18, No.1, pp. 44-50, 2006.
Data files:
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