International Journal of Trend in Scientific Research and Development (IJTSRD) Volume 4 Issue 1, December 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470 @ IJTSRD | Unique Paper ID – IJTSRD29626 | Volume – 4 | Issue – 1 | November-December 2019 Page 637 Motion Control of Mobile Robots using Fuzzy Controller Halil Çetin 1 , Akif Durdu 2 1,2 Department of Electrical and Electronics Engineering, 1 Konya Technical University, Konya, Türkiye 2 Ohio State University, Columbus, USA ABSTRACT In this study, a motion control based on fuzzy logic is designed so that mobile robots can make the turns they make when moving in an unknown environment more flexibly and smoothly. Fuzzy logic control is suitable for controlling mobile robots because the results can be obtained under uncertainty. Fuzzy logic control is implemented through a set of rules created using expert knowledge. The fuzzy rules created in this paper are designed to allow mobile robots to escape from obstacles, to avoid contact with walls, and to make soft turns without harming their structure. According to the obtained simulation results, the mobile robot has been shown to have successful results in fuzzy logic based motion control. KEYWORDS: fuzzy logic; fuzzy logic controller; mobile robot; simulation; motion control How to cite this paper: Halil Çetin | Akif Durdu "Motion Control of Mobile Robots using Fuzzy Controller" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1, December 2019, pp.637-641, URL: www.ijtsrd.com/papers/ijtsrd29626.pdf Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by /4.0) I. INRODUCTION Mobile robots are mechanical devices that are capable of moving autonomously in a given environment. The autonomous movement of the robots is achieved by taking the information in the environment by using the distance sensors or imaging methods. The most common sensors are the distance sensors (ultrasonic, laser, etc.) that have the ability to measure distances to obstacles in the paths that robots follow. Advanced autonomous robots have to be equipped with abilities when they are left in a certain environment, moving along the corridor, following the walls, turning round the corners and entering the open spaces of the rooms [1]. The autonomous moving robots that have existed since the 1950s have been used primarily for the storage of factories and cargoes in mining. Today, the development of technology and especially the development of signal processing technology, the use of mobile robots has become widespread. Especially in the defense industry, it has had an important place in search and rescue operations and space exploration. Generally, to be able to act autonomously of wheeled mobile robot is based on a computer or sensors help the processor and the engine driven by perceptions around him [2]. Many researchers used fuzzy logic approach for mobile robot movements. Raguraman et al. [3] simulated motion of the mobile robot which has sensors by using fuzzy logic. They stated that the mobile robot can avoid obstacles and follow a trajectory. Sang et al. [1] used fuzzy logic to control movement of a sensor-based wheeled robot along a predefined path. Gaonkar et al. [4] used fuzzy logic to develop intelligent autonomous mobile robots using sensors to counter unexpected changes in the environment and to avoid obstacles. Mobile robots are used in many applications; they move in dynamic environment having unknown obstacles instead of moving on a predetermined route. Considering this situation, robots, which can detect the obstacles that are not affected by the changes that may occur in the environment and reach their targets without hitting them and damaging their mechanical parts, should be designed. In this study, a robot that can be operated in a dynamic environment is realized in a fuzzy logic based motion control simulation environment. The inputs of the fuzzy logic controller are the values of the front, right and left ultrasonic sensors of the robot and the angle of the target direction, and the output of the controller is the rotation angle of the mobile robot. A control model was created in accordance with the data given from the sensors. A series of fuzzy logic rules have been developed based on expert knowledge under various circumstances. In the following sections of this paper, the applied fuzzy logic control method first will be mentioned, and then the simulation and the results obtained will be given and the future work plan will be explained. II. FUZZY LOGIC CONTROL Zadeh [5] suggested a method of modeling human logic using fuzzy arrays. Some features that may be mentioned for fuzzy logic; i) uses certain information in a systematic way, ii) it IJTSRD29626