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Article

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

1
Department of Computer Science & Information Engineering, Nation Cheng Kung University, Tainan 701, Taiwan
2
Department of Computer Science & Information Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(12), 4181; https://doi.org/10.3390/s18124181
Received: 20 October 2018 / Revised: 23 November 2018 / Accepted: 24 November 2018 / Published: 28 November 2018
(This article belongs to the Special Issue Mobile Robot Navigation)
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. View Full-Text
Keywords: evolutionary robot; navigation control; fuzzy control; wall-following control; cooperative carrying; interval type-2 neural fuzzy controller; artificial bee colony algorithm; grouping strategy evolutionary robot; navigation control; fuzzy control; wall-following control; cooperative carrying; interval type-2 neural fuzzy controller; artificial bee colony algorithm; grouping strategy
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MDPI and ACS Style

Lin, C.-H.; Wang, S.-H.; Lin, C.-J. Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments. Sensors 2018, 18, 4181. https://doi.org/10.3390/s18124181

AMA Style

Lin C-H, Wang S-H, Lin C-J. Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments. Sensors. 2018; 18(12):4181. https://doi.org/10.3390/s18124181

Chicago/Turabian Style

Lin, Chun-Hui, Shyh-Hau Wang, and Cheng-Jian Lin. 2018. "Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments" Sensors 18, no. 12: 4181. https://doi.org/10.3390/s18124181

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