Simulation of Obstacle Detection and Speed Control for Autonomous Robotic Vehicle
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Abstract
This chapter introduces a digital image processing algorithm to detect the obstacle in the path and according to the position of the obstacle, the speed of Autonomous Robotic Vehicle is controlled through PID based Speed control module. The camera mounted on Autonomous Robotic Vehicle captures image in such a way that the obstacle in image and actual vehicle position keep some distance to avoid collision. Based on the computed obstacle size, the vehicle actions are controlled. The streaming of the images of the path is done and each image is analysed through MATLAB Simulink based Video Processing Module. The control actions are taken based on the PID constants computed through MATLAB Simulink modules.
Keywords
Autonomous Robotic Vehicle (ARV) Digital image processing Speed control PID control Simulation MATLAB Simulink Permanent Magnet Direct Current (PMDC) motorReferences
- 1.M. Buehler, K. Lagnemma, S. Singh, The DARPA Urban Challenge Autonomous Vehicles in City Traffic (Springer) pp. 202–247 (2009)Google Scholar
- 2.R.A. Hamzah, H.N. Rosly, S. Hamid, An Obstacle Detection and Avoidance of A Mobile Robot with Stereo Vision Camera, in 2011 International Conference on Electronic Devices, Systems and Applications (ICEDSA) Google Scholar
- 3.S. Badal, S. Ravela, B. Draper, A. Hanson, A Practical Obstacle Detection and Avoidance System, IEEE, pp. 97–104 (1994)Google Scholar
- 4.X. Zhang, Y. Zhang, An Obstacle Detection Method based on Machine Vision. IEEE (2010)Google Scholar
- 5.H. Hashimoto, T. Yamaura, M. Higashiguchi, Detection of Obstacle from Monocular Vision based on Histogram Matching Method. IEEE 1996, pp. 1047–1051 (1996)Google Scholar
- 6.R.C. Gonzalez, R.E. Woods, Digital Image Processing, 2nd edn (Prentice-Hall, Upper Saddle River), pp. 64–66, 567–624 (2002)Google Scholar
- 7.M. Anji Reddy, Y. Hari Shankar, Textbook of Digital Image Processing (BS Publications, Hyderabad), pp. 26–53 (2006)Google Scholar
- 8.E.R. Davies, Machine Vision-Theory, Algorithms and Practicalities, 2nd edn (Academic Press, London), pp. 79–85, 103–128, 437–440Google Scholar
- 9.S.W. Sung, J. Lee, I.B. Lee, Process Identification and PID Control (Wiley, Singapore), pp. 111–120Google Scholar
- 10.R. Lacoste, PID Control Without Math. http://itech.fgcu.edu/faculty/zalewski/CDA4170/files/PIDcontrol.pdf. 25 July 2012
- 11.T. Wescott, PID Without a PhD. http://igor.chudov.com/manuals/Servo-Tuning/PID-without-a-PhD.pdf. 25 July 2012
- 12.Control System Toolbox 9.1. http://www.mathworks.in/help/toolbox/control/control_product_page.html. July 25 2012
- 13.M. Meenakshi, Microprocessor based PID Controller for Speed Control of DC Motor”, IEEE Computer Society, in International Conference on Emerging Trends in Engineering and Technology, pp. 960–965Google Scholar
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