Publication Type : Conference Paper
Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics,
Source : 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Institute of Electrical and Electronics Engineers Inc., Volume 2017-January, p.1660-1664 (2017)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042682281&doi=10.1109%2fICACCI.2017.8126081&partnerID=40&md5=e01e1945e480f7894f6033d8f2ad4d59
ISBN : 9781509063673
Keywords : Adaptive neuro-fuzzy inference system, CANFIS, Collision-free paths, Fuzzy inference, Fuzzy neural networks, Fuzzy systems, Infrared detectors, Infrared devices, Mobile robots, Navigation, Navigation problem, Obstacle, Robotic navigation, Robots, Sensors, Steeringangle, Uncertain environments
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Mechanical Engineering
Year : 2017
Abstract : This paper aims at developing a sensor-based Co-Active adaptive neuro-fuzzy inference system (CANFIS) for solving navigation problems of the mobile robot in an uncertain environment. The infrared sensor reads the distances of right, front and left obstacle. The collision-free path is accomplished by CANFIS controller which selects the desired steering angle by construing the obstacle distance information measured by the infrared sensor. The simulation of CANFIS based algorithm provides more precise steering angle, which implements the navigation task securely and efficiently in an environment populated with static obstacles. © 2017 IEEE.
Cite this Research Publication : K. V. Geedhu, Dr. K. I. Ramachandran, and Adarsh, S., “CANFIS based robotic navigation”, in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, 2017, vol. 2017-January, pp. 1660-1664.