Mobile Robot Navigation Using Open Computer Vision with Fuzzy Controller

Julirose Gonzales; Zahari Taha

doi:10.20965/jaciii.2008.p0336

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JACIII Vol.12 No.4 pp. 336-341

doi: 10.20965/jaciii.2008.p0336

(2008)

Paper:

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Mobile Robot Navigation Using Open Computer Vision with Fuzzy Controller

Julirose Gonzales and Zahari Taha

Department of Engineering Design & Manufacture University Malaya, Kuala Lumpur, Malaysia

Received:

April 23, 2007

Accepted:

June 27, 2007

Published:

July 20, 2008

Keywords:

robot navigation, computer vision, fuzzy control, obstacle avoidance

Abstract

This research presents a fuzzy controller technique in navigation with obstacle avoidance for a general purpose mobile robot in a given global environment with image processing technique using Open Source Computer Vision (OpenCV) library on Visual C++. Fuzzy Logic is used to control the navigation of the robot towards the goal while avoiding obstacles along the way by changing its direction of movement. The positions of the mobile robot, obstacle and the destination are taken into consideration and an overhead camera (above the robot’s environment) is used to gather these necessary information. The images captured are processed using different techniques to get the desired positions and is directly integrated with the fuzzy controller making the algorithm more efficient compared to other vision-guided navigation techniques.

Cite this article as:

J. Gonzales and Z. Taha, “Mobile Robot Navigation Using Open Computer Vision with Fuzzy Controller,” J. Adv. Comput. Intell. Intell. Inform., Vol.12 No.4, pp. 336-341, 2008.

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References

[1] M. Y. Ibrahim and A. Fernandes, “Study on Mobile Robot Navigation Techniques,” Proc. of 2004 IEEE Int. Conf. on Industrial Technology.
[2] E. Dadios and O. Maravillas, “Cooperative Mobile Robots with Obstacle and Collision Avoidance Using Fuzzy Logic,” Proc. of 2002 IEEE Int. Symposium on Intelligent Control, Vancouver, Canada.
[3] L. Zadeh, “Fuzzy Sets,” Information and Control Vol.3, 1965.
[4] E. H. Mamdani, “Application of Fuzzy Algorithm for the Control of a Dynamic Plant,” IEEE Proc., Vol.21, pp. 1585-1588, 1974.
[5] N. Otsu, “A Threshold Selection Method from Gray-Level Histograms,” IEEE Transactions on Systems, Man, and Cybernetics, Vol.9, No.1, pp. 62-66, 1979.
[6] J. Parker, “Algorithms for Image Processing and Computer Vision,” New York, John Wiley & Sons, Inc., pp. 23-29, 1997.
[7] T. Gevers et. al, “ Color-based Object Recognition,” Pattern Recognition Vol.32 pp. 453-464, 1999.
[8] G. Anderson, “Fundamentals of Fuzzy Logic: Parts 1,2,3,” SENSORS, March-May 1993
[9] C. Stachniss and W. Burgard, “An integrated approach to goaldirected obstacle avoidance under dynamic constraints for dynamic environments,” Intelligent Robots and System, 2002. IEEE/RSJ Vol.1, Oct, pp. 508-513, 2002.
[10] E. Dadios and O. Maravillas, “Fuzzy Logic Controller for microrobot soccer game,” Proc. of the Industrial Electronics Conf. , Denver, Colorado, USA, pp. 2154-2159, 2001.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] M. Y. Ibrahim and A. Fernandes, “Study on Mobile Robot Navigation Techniques,” Proc. of 2004 IEEE Int. Conf. on Industrial Technology.

[2] [2] E. Dadios and O. Maravillas, “Cooperative Mobile Robots with Obstacle and Collision Avoidance Using Fuzzy Logic,” Proc. of 2002 IEEE Int. Symposium on Intelligent Control, Vancouver, Canada.

[3] [3] L. Zadeh, “Fuzzy Sets,” Information and Control Vol.3, 1965.

[4] [4] E. H. Mamdani, “Application of Fuzzy Algorithm for the Control of a Dynamic Plant,” IEEE Proc., Vol.21, pp. 1585-1588, 1974.

[5] [5] N. Otsu, “A Threshold Selection Method from Gray-Level Histograms,” IEEE Transactions on Systems, Man, and Cybernetics, Vol.9, No.1, pp. 62-66, 1979.

[6] [6] J. Parker, “Algorithms for Image Processing and Computer Vision,” New York, John Wiley & Sons, Inc., pp. 23-29, 1997.

[7] [7] T. Gevers et. al, “ Color-based Object Recognition,” Pattern Recognition Vol.32 pp. 453-464, 1999.

[8] [8] G. Anderson, “Fundamentals of Fuzzy Logic: Parts 1,2,3,” SENSORS, March-May 1993

[9] [9] C. Stachniss and W. Burgard, “An integrated approach to goaldirected obstacle avoidance under dynamic constraints for dynamic environments,” Intelligent Robots and System, 2002. IEEE/RSJ Vol.1, Oct, pp. 508-513, 2002.

[10] [10] E. Dadios and O. Maravillas, “Fuzzy Logic Controller for microrobot soccer game,” Proc. of the Industrial Electronics Conf. , Denver, Colorado, USA, pp. 2154-2159, 2001.