Browse > Article
http://dx.doi.org/10.6109/jkiice.2011.15.4.759

Navigation Control of Mobile Robot based on VFF to Avoid Local-Minimum in a Corridor Environment  

Jin, Tae-Seok (동서대학교 메카트로닉스공학과)
Abstract
This paper deals with the method of using the amended virtual force field technique to avoidance the front environment(wall, obstacles etc.) in navigating by using the environmental informations recognized by a ultrasonic-ring and pan/tilt CCD camera equipped on a mobile robot. we will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. It is proposed the rusult from the experimental run based on a virtual force field(VFF) method to support the validity of the aforementioned architecture of mobile service robot for local navigation and obstacle avoidance for autonomous mobile robots. We will conclude by discussing some possible future extensions of the project. The results show that the proposed algorithm is apt to identify obstacles in an indoor environments to guide the robot to the goal location safely.
Keywords
mobile robot; indoor navigation; obstacle avoidance; multi-sensor; recognition;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Brooks, R. A. "A Robust Layered Control System for a Mobile Robot", IEEE Journal of Robotics and Automation RA-2, 1986, pp.14-23
2 A. Yilmaz, O. Javed, and M. Shah, "Object tracking: a survey," ACM Computing Surveys, vol. 38, no. 4, 2006.
3 K.S. Tseng and C.W. Tang, "Self-localization and stream field based partially observable moving object tracking," EURASIP Journal on Advances in Signal Processing, vol. 2009, Article ID 416395, 12 pages, 2009.
4 Y. Koren and J. Borenstein, "Potential field methods and their inherent limitations for mobile robot navigation," in Proc. IEEE International Conference on Robotics and Automation, vol. 2, 1991.
5 J. Borenstein and Y. Koren, "The vector field histogram-fast obstacle avoidance for mobilerobots," IEEE Transactions on Robotics and Automation, vol. 7, no. 3, pp. 278-278, 1991.   DOI   ScienceOn
6 I. Ulrich and J Borenstein, "VFH^*: Local obstacle avoidance with look-ahead verification," in Proc. IEEE International Conference on Robotics and Automation, pp. 2505-2511, April 2000.
7 K.-Y. Im and S.-Y. Oh, "An extended virtual force field based behavioral fusion with neural networks and evolutionary programming for mobile robot navigation," in Proceedings of the 2000 Congress on Evolutionary Computation, vol. 2, pp. 1238-1244, 2000.
8 Johann Borenstein, "Real-Time Obstacle Avoidance for Fast Mobile Robots", IEEE Transactions on Systems, Man and Cybernetics, vol. 19, No. 5, September/October, 1989.
9 J. C. Alexander and J. H. Maddocks, "On the kinematics of wheeled mobile robots", Int. J. of Robotics Research, vol. 8, no. 5,pp. 15-27, 1989.   DOI
10 Jun Tani and Naohiro Fukumura, "Learing Goal-Directed Sensory-Based Navigation of a Mobile Robot", Neural Networks, vol.7, No.3, 1994, pp. 553-563.   DOI   ScienceOn