Publication Type:

Conference Paper

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)

ISBN:

9781509063673

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042682281&doi=10.1109%2fICACCI.2017.8126081&partnerID=40&md5=e01e1945e480f7894f6033d8f2ad4d59

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

Abstract:

<p>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.</p>

Notes:

cited By 0; Conference of 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 ; Conference Date: 13 September 2017 Through 16 September 2017; Conference Code:133501

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.