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Issue title: Special section: Decision Making Using Intelligent and Fuzzy Techniques
Guest editors: Cengiz Kahraman
Article type: Research Article
Authors: Sezgin, Anıl | Çetin, Ömer; *
Affiliations: National Defense University, Hezârfen Aeronautics and Space Technologies Institute, Turkey
Correspondence: [*] Corresponding author. Ömer Çetin, National Defense University, Hezârfen Aeronautics and Space Technologies Institute, Turkey. E-mail: [email protected].
Abstract: The autonomous navigation problem is currently a popular research topic encountered in many different areas, from smart cars to automated warehouse operations. Autonomous navigation of robotic systems is examined in two basic areas, with and without external supports. Even if the robot uses external supports (like GPS, road signs, ground surface lines, barcodes etc.) or positioning itself with internal sensors (like gyro, IMU, etc.), it independently needs a control method to follow the desired route. When the widely used control approaches in the literature are examined, PID and fuzzy-based approaches are frequently encountered. They both offer advantages and disadvantages. Within the scope of this study, the positive aspects of both of control approaches are utilized and the hybrid control approach for a robot that can autonomously follow the ground line presented as an external reference is mentioned. The success of the approach was tested comparatively on an exemplary mobile platform. The applied results obtained experimentally showed that a more efficient fuzzy logic-based hybrid control method could be developed. In addition, the effect of the number of conditions in the rule table on the success of the hybrid control technique is shown in the study. It has also been experimentally demonstrated that the success of hybrid control approach with a limited low power consuming ARM based processor that is suitable to control most of lightweight mobile platforms.
Keywords: Autonomous line follower robot, fuzzy control, PD control, hybrid control
DOI: 10.3233/JIFS-189076
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6021-6031, 2020
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