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{"references": ["Mobile Robotics. (2009, September 7). Retrieved September 27, 2009,\nfrom Wikipedia: http://en.wikipedia.org/wiki/Mobile_robotics", "FIRST Robotics. (2009, May 13). FIRST At A Glance. Retrieved\nSeptember 27, 2009, from USFIRST.org:\nhttp://www.usfirst.org/aboutus/content.aspx?id=160", "Trinity College. (2009, September 26). Firefighting Home Robot\nContest. Retrieved September 27, 2009, from Trinity College:\nhttp://www.trincoll.edu/events/robot/", "Tahboub, K. K., & Al-Din, M. S. (2009). A Neuro-Fuzzy Reasoning\nSystem for Mobile Robot Navigation. Jordan Journal of Mechanical and\nIndustrial Engineering , 3 (1), 77-88.", "Zein-Sabatto, S., Sekmen, A., & Koseeyaporn, P. (2003). Fuzzy\nBehaviors for Control of Mobile Robots. Systemics, Cybernetics and\nInformatics, 1 (1), 68-74.", "Black, P. E. (1999). Algorithms and Theory of Computation Handbook.\nBoca Raton, FL: CRC Press LLC.", "Bullinaria, J. A. (2002, November 18). Implementing a Neural Network\nin C. Retrieved September 2, 2009, from School of Computer Science;\nThe University of Birmingham, UK:\nhttp://www.cs.bham.ac.uk/~jxb/NN/nn.html"]}
A robot simulator was developed to measure and investigate the performance of a robot navigation system based on the relative position of the robot with respect to random obstacles in any two dimensional environment. The presented simulator focuses on investigating the ability of a fuzzy-neural system for object avoidance. A navigation algorithm is proposed and used to allow random navigation of a robot among obstacles when the robot faces an obstacle in the environment. The main features of this simulator can be used for evaluating the performance of any system that can provide the position of the robot with respect to obstacles in the environment. This allows a robot developer to investigate and analyze the performance of a robot without implementing the physical robot.
Applications of Fuzzy Logic and Neural Networksin Robotics, MobileRobots, Artificial Intelligence, Robot Navigation, Robotics., Embedded Systems
Applications of Fuzzy Logic and Neural Networksin Robotics, MobileRobots, Artificial Intelligence, Robot Navigation, Robotics., Embedded Systems
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