Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments

作     者：Lin, Chun-Hui Wang, Shyh-Hau Lin, Cheng-Jian 

作者机构：Nation Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan Natl Chin Yi Univ Technol Dept Comp Sci & Informat Engn Taichung 411 Taiwan 

出 版 物：《SENSORS》 (传感器)

年 卷 期：2018年第18卷第12期

页      面：4181-4181页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基　　金：Ministry of Science and Technology of the Republic of China  Taiwan [MOST 106-2221-E-167-016] 

主　　题：evolutionary robot navigation control fuzzy control wall-following control cooperative carrying interval type-2 neural fuzzy controller artificial bee colony algorithm grouping strategy 

摘      要：In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.