Automated Navigation System based on Weapon-Target Assignment

Gayuh Titis Permana, Maman Abdurohman, Mohammad Khairudin, Mohammad Lutfi

Abstract


Operating of weapon on the tank is mostly by manually. It is not desired performance for a critical operation. An automatic control system is required to operate the weapon with the target while maintaining the accuracy. In this paper has designed an automatic weapon control system using object image proccessing. Various an image processing methods used to improve the weapon accuracy to obtain the intended target. The method used in digital image processing is the Camshift motion tracking method. This method is compared with the Lucas Canade motion tracking method. This comparison is conducted to found more precise results between the two methods. Results of object image processing are used to control the direction of the weapon that towards the desired goal. The results show that the implementation of the Lucas Canade motion tracking method using fire simulation tools have been successful. The performance of the Lucas Canade motion tracking methods is better than the CamShift method. Using Lucas Canade method for weapon controller is accordance with the purposes.


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References


Cai H, Liu J, Chen Y, and Wang H. Survey of the research on dynamic weapon-target assignment problem. Journal of Systems Engineering and Electronics. 2006; 17(3): 559-565.

Lee Z. J., Lee C. Y. and Su S. F. An immunity-based ant colony optimization algorithm for solving weapon–target assignment problem. Journal of Applied Soft Computing. 2002; 2: 39-47.

Shang G. Solving Weapon-Target Assignment Problems by a New Ant Colony Algorithm. Proceeding of International Symposium on Computational Intelligence and Design. 2008. 221-224.

Wacholder E. A neural network-based optimization algorithm for the static weapon-target assignment problem. ORSA Journal on Computing. 4(1989): 232-246.

Alfiansyah A. A Unified Energy Approach for B-Spline Snake in Medical Image Segmentation. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2010; 8(2): 175-186.

Firdausy K, Riyadi S, Sutikno T, Muchlas. Aplikasi Webcam untuk sistem pemantauan ruang berbasis Web. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2008; 6(1): 39-48.

Zhou H., Yuan Y. and Shi C. Object tracking using sift features and mean shift. Journal of Computer Vision and Image Understanding. 113(2009); 345-352.

SLi S. X., Chang H.C. and Zhu C. F. Adaptive pyramid mean shift for global real-time visual tracking. Journal of Image and Vision Computing. 28(2010): 424-437.

Djajadi A, Laoda F, Rusyadi R, Prajogo T, Sinaga M. A Model Vision of Sorting System Application Using Robotic Manipulator. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2010; 8(2): 137-148.




DOI: http://doi.org/10.12928/telkomnika.v9i3.735

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