A Goal Oriented Navigation System Using Vision


  • Mehmet Serdar Güzel Computer Engineering Department, Ankara University, Turkey
  • Panus Nattharith Department of Electrical and Computer Engineering, Faculty of Engineering, Naresuan University, Thailand.
  • Ahmet S. Duran Computer Engineering Department, Ankara University, Turkey


Goal-Oriented Navigation, Mobile Robots, Monocular Vision, Behavioral Design,


This paper addresses a goal oriented navigation framework in a behavior-based manner for autonomous systems. The framework is mainly designed based on a behavioral architecture and relies on a monocular vision camera to obtain the location of goal. The framework employs a virt ual physic based method to steer the robot towards the goal while avoiding unknown obstacles, located along its path. Simulation results validate the performance of the proposed framework.


DeSouza G. N. and Kak A. C., 2002. Vision for mobile robot navigation: a survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(2): 237-267.

Guzel M. S., 2013. Autonomous vehicle navigation using vision and maples strategies: A survey, Hindawi Publishing Corporation Advances in Mechanical Engineering: 1-10.

Hashima M., Hasegawa F., Kanda S., Maruyama T. and Uchiyama T., 1997. Localization and obstacle detection for a robot for carrying food trays, Proceedings of the IEEE/RSJ International Conference on Intelligent Robot and Systems (IROS ’97): 345-351.

Sawasaki N. Morita T., and Uchiyama T., 1996. Design and implementation of high-speed visual tracking system for real-time motion analysis, Proceedings of the IAPR International Conference Pattern Recognition, 3: 478-483.

Kabuka M. R. and Arenas A. E., Position verification of a mobile robot using standard pattern, IEEE Journal of Robotics and automation, 3(6):505-516.

Guzel M. S. and Bicker R., 2010. Optical flow based system design for mobile robots, Proceedings of the IEEE International Conference on Robotics, Automation and Mechatronics (RAM ’10): 545-550.

Bonin-Font F. Ortiz A., and Oliver G., 2008. Visual navigation for mobile robots: a survey, Journal of Intelligent and Robotic Systems,53(3): 263-296.

Ulrich I. and Nourbakhsh I., 2000. Appearance – based obstacle detection with monocular color vision, Proceedings of the AAAI National Conference on Artificial Intelligence.

Szenher D. M., 2008. Visual homing in dynamic indoor environments [Ph.D. thesis], University of Edinburgh, Edinburgh, UK.

Harrell R. C., Slaughter D. C., and Adsit P. D., 1989. A fruit – tracking system for robotic harvesting, Machine Vision and Applications, 2(2): 69-80.

Brooks, R. A., 1986. Robust Layered Control System for a Mobile Robot, IEEE Journal of Robotics and Automation, RA-2: 14-23.

Arkin R. C., 1998. Behavior – Based Robotics, MIT Press, Cambridge, Massachusetts

Brooks, R. A., 1999. Cambrian Intelligence: The Early History of the New AI. MIT Press, Cambridge, Massachusetts.

Guzel, M. S. and Nattharith, P., 2014. A New Technique for Distance Estimation using SIFT for Mobile Robots, International Electrical Engineering Congress (iEECON 2014).




How to Cite

Serdar Güzel, M., Nattharith, P., & S. Duran, A. (2017). A Goal Oriented Navigation System Using Vision. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-3), 73–76. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2276