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http://dx.doi.org/10.9717/kmms.2015.18.3.387

Fuzzy Logic Based Auto Navigation System Using Dual Rule Evaluation Structure for Improving Driving Ability of a Mobile Robot  

Park, Kiwon (Dept. of Green Automobile Engineering, School of Engineering Youngsan University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.3, 2015 , pp. 387-400 More about this Journal
Abstract
A fuzzy logic based mobile robot navigation system was developed to improve the driving ability without trapping inside obstacles in complex terrains, which is one of the most concerns in robot navigation in unknown terrains. The navigation system utilizes the data from ultrasonic sensors to recognize the distances from obstacles and the position information from a GPS sensor. The fuzzy navigation system has two groups of behavior rules, and the robot chooses one of them based on the information from sensors while navigating for the targets. In plain terrains the robot with the proposed algorithm uses one rule group consisting of behavior rules for avoiding obstacle, target steering, and following edge of obstacle. Once trap is detected the robot uses the other rule group consisting of behavior rules strengthened for following edge of obstacle. The output signals from navigation system control the speed of two wheels of the robot through the fuzzy logic data process. The test was conducted in the Matlab based mobile robot simulator developed in this study, and the results show that escaping ability from obstacle is improved.
Keywords
Robot Navigation; Fuzzy Systems; Fuzzy Logic Controller;
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