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Obstacle Avoidance for a Mobile Robot Using Optical Flow  

Lee, Han-Sik (OpenVisual, Inc.)
Baek, Jun-Geol (Department of Industrial Systems Engineering, Induk Institute of Technology)
Jang, Dong-Sik (Department of Industrial Systems and Information Engineering, Korea University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.28, no.1, 2002 , pp. 25-35 More about this Journal
Abstract
This paper presents a heuristic algorithm that a mobile robot avoids obstacles using optical flow. Using optical flow, the mobile robot can easily avoid static obstacles without a prior position information as well as moving obstacles with unknown trajectories. The mobile robot in this paper is able to recognize the locations or routes of obstacles, which can be detected by obtaining 2-dimensional optical flow information from a CCD camera. It predicts the possibilities of crash with obstacles based on the comparison between planned routes and the obstacle routes. Then it modifies its driving route if necessary. Driving acceleration and angular velocity of mobile robot are applied as controlling variables of avoidance. The corresponding simulation test is performed to verify the effectiveness of these factors. The results of simulation show that the mobile robot can reach the goal with avoiding obstacles which have variable routes and speed.
Keywords
obstacle avoidance; optical flow; mobile robot; fuzzy logic;
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  • Reference
1 Song, K. and Tai, J. (1992), Fuzzy Navigation of a Mobile Robot, Proceeding of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, 621-627
2 Borenstein, J. and Koren, Y. (1989), Real-time obstacle avoidance for fast mobile robot, IEEE Transactions on Systems, Man, Cybernetics, 19(5), 1179-1187
3 Khatib, O. (1986), Real-time obstacle avoidance for manipulators and mobile robots, International Journal of Robotics Research, 5(1), 90-98   DOI   ScienceOn
4 Moravec, H. P. and Elfes, A. (1985), High Resolution Maps from Wide Angle Sonar, Proceedings of IEEE Conference on Robitics and Automation, 116-121
5 Sonka, M., Hlavac, V. and Boyle, R. (1993), Image Processing, Analysis and Machine Vision, Chapman & Hall Computing
6 Beaufrere, B. and Zeghloul. S. (1995), Navigation Method for a Mobile Robot Using Fuzzy-based Method, International Journal of Robotics and Automation, 10(3)
7 Horn, B. and Schunck, B. (1983), Determining optical flow, Artifical Intelligence, 17, 185-203
8 Camus, T. (1994), Real-time Optical Flow, MVA/SME Applied Machine Vision 94
9 Larcommbe, M. H. E. (1981), Tracking stability of wire guided vehicles, Proceedings of International Conference on Automated Guided Vehicle System, 137-144
10 Brooks, R. A. (1986), A robust layered control system for a mobile robot, IEEE Transactions on Robotics and Automation, 2(1), 14-23
11 Boom, H. R. and Cho, H. S. (1992), A sensor- based obstacle avoidance controller for a mobile robot using fuzzy logic and neural network, IEEE International Conference on Intelligent Robots and Systems, 1470-1475
12 Enkelmann, W. (1991), Obstacle detection by evaluation of optical flow fields from image sequences, Image and Vision Computing, 9(3), 160-168   DOI   ScienceOn
13 Lee, K-H. and Oh, K-R. (1991), Fuzzy Logics and Applications, Hongneung Publishing Co