Fuzzy behavior-based control trained by module learning to acquire the adaptive behaviors of mobile robots

作     者：Izumi, K Watanabe, K 

作者机构：Saga Univ Fac Sci & Engn Dept Mech Engn Saga 8408502 Japan Saga Univ Grad Sch Sci & Engn Dept Adv Syst Control Engn Saga 8408502 Japan 

出 版 物：《MATHEMATICS AND COMPUTERS IN SIMULATION》 (系统模拟中的数学与计算机)

年 卷 期：2000年第51卷第3-4期

页      面：233-243页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0835[工学-软件工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：behavior-based control module learning subsumption architecture genetic algorithm fuzzy set theory mobile robot 

摘      要：Intelligent control techniques for robotic systems have been used with some success in a wide variety of applications. In this paper, we construct a method for the intelligent control system of a robot using the fuzzy behavior-based control, which decomposes the control system into several elemental behaviors, and each one is realized by fuzzy reasoning. In particular, a module learning method is investigated for obtaining each representative group behavior, so that the robot can, consequently, acquire more general knowledge or fuzzy reasoning, than a central learning method. The proposed method is applied for an obstacle-avoidance problem of a mobile robot;the effectiveness of the method is illustrated through some simulations. (C) 2000 IMACS/Elsevier Science B.V. All rights reserved.