標題: Using a Type-2 Neural Fuzzy Controller for Navigation Control of Evolutionary Robots
作者: Lin, Cheng-Jian
Jhang, Jyun-Yu
Young, Kuu-Young
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: mobile robot;type-2 fuzzy neural controller;whale optimization algorithm;navigation control;wall-following control
公開日期: 1-一月-2019
摘要: In this paper, we present an effective navigation control method for mobile robots in an unknown environment. The proposed behavior manager (BM) switches between two behavioral control patterns, wall-following behavior (WFB) and toward-goal behavior (TGB), on the basis of the relationship between the mobile robot and the unknown environment. A type-2 neural fuzzy controller (T2NFC) with an improved whale optimization algorithm (IWOA) is proposed to provide WFB control and obstacle avoidance for mobile robots. In the WFB learning process, the input signal of a controller is the distance between the wall and the sonar sensors, and its output signal is the speed of two wheels of a mobile robot. A fitness function, which operates on the total distance traveled by the mobile robot, distance from the side wall, angle to the side wall, and moving speed, evaluates the WFB performance of the mobile robot. Experimental results reveal that the proposed IWOA is superior to other methods of WFB and navigation control.
URI: http://dx.doi.org/10.18494/SAM.2019.2343
http://hdl.handle.net/11536/152897
ISSN: 0914-4935
DOI: 10.18494/SAM.2019.2343
期刊: SENSORS AND MATERIALS
Volume: 31
Issue: 9
起始頁: 2735
結束頁: 2751
顯示於類別:期刊論文