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[2] Nugraha, Aditya. “Modifikasi Particle Swarm Optimization untuk Pencarian Banyak Sumber Asap dengan Visualisasi”. Skripsi FASILKOM, Universitas Indonesia. 2008.
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[6] Martinoli, Hayes, A., A.T., Goodman, R.M (2003). Swarm robotic odorlocalization: Off-line Optimization and validation with real robots. Robotica.
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[9] Efendi, Rusdi. “Modifikasi Algoritma Particle Swarm Optimization untuk Pencarian Multi Sumber Gas: Simulasi dan Analisis”. Tesis FASILKOM, Universitas Indonesia. 2008.
[10] Nugraha, A., W. Jatmiko, dan J. Perkasa. “Modifikasi Particle Swarm Optimization untuk Pencarian Banyak Sumber Gas”. Jurnal Ilmu Komputer dan Informasi. Juli 2008.
[11] Jatmiko, W., Febrian, A., Jovan, F., Suryana, M.E., Insani, A. (2010). Swarm Robot dalam Pencarian Sumber Asap, UI Press.
[12] Hinze, J.O., Turbulance. McGraw-Hill, 1995.
[13] Wisnu Jatmiko, and Toshio Fukuda, and Takayuki Matsuno, and Fumihito Arai, and Benyamin Kusumoputro. (2005). Robotic Applications for Odor-Sensing Technology: Progress and Challenge. WSEAS TRANSACTIONS on SYSTEMS.
[14] Martinoli, Hayes, A., A.T., Goodman, R. M. (2002). Distributed odor source localization. IEEE Sensors.
[15] Martinoli, Hayes, A., A.T., Goodman, R. M. (2003). Swarm robotic odor localization: Off-line optimization and validation with real robots. Robotica.
[16] Belanger, J.H., Wilis, M.A. (1998). Biologically-inspired search algorithms for locating unseen odor sources. In Proceedings of the 1998 IEEE ISIS/CIRA/ISAS Joint Conference on the Science and Technology of Intelligent Systems.
[17] Engelbrecht Andries P. (2005). Fundamentals of Computational Swarm Intelligence. Wiley.
[18] Blackwell, T. M., Bentley, P. J. (2004). Dynamic search with charged swarms. In Proceedings of the Genetic and Evolutionary Computation Conference.
[19] Blackwell, T. M. (2002). Swarms in dynamic environment. In Proceedings of the Genetic and Evolutionary Computation.
[20] Blackwell, T. M., and Bentley, P. J. (2002). Dont push me! collision-avoiding swarms. In Proceedings of the IEEE Congress on Evolutionary Computation.
[21] F. W. Aribowo and I. Setiawan, -Penjejak ArahCahaya Dengan Kendali Logika, J. Tek. elektro, pp. 144–150, 2008.
[22] S. A. El-teleity, -Fuzzy Logic Control of an Autonomous MobileRobot, pp. 188–193, 2011.
[23] da S. Henrique V, C. K. Morooka, I. R. Guilherme, T. C. Fonseca, and J. R. P. Mendes, -Leak detection in petroleum pipelines using a fuzzy system, ELSEVIER, J. Pet. Sci. Eng., vol. 49, pp. 223–238, 2005.
[2] Nugraha, Aditya. “Modifikasi Particle Swarm Optimization untuk Pencarian Banyak Sumber Asap dengan Visualisasi”. Skripsi FASILKOM, Universitas Indonesia. 2008.
[3] Pambuko, Wulung. “Modifikasi Particle Swarm Optimization untuk pencarian banyak sumber asap dengan Open Dynamic Engine”. Tesis FASILKOM, Universitas Indonesia. 2009.
[4] Eberhart, R.C., dan J. Kennedy. “A New Optimizer Using Particle Swarm Theory”. Proceeding of the 6th International Sysmposiumon Micromachine and Human Science
[5] Jatmiko, W., Jovan F, Dhiemas R.Y. S , T. Fukada, K. Sekiyama. (2010) . Robots Implementation for Odor Source Localization Using PSO Algorithm. WSEAS Transaction on Circuits and Systems
[6] Martinoli, Hayes, A., A.T., Goodman, R.M (2003). Swarm robotic odorlocalization: Off-line Optimization and validation with real robots. Robotica.
[7] Eberhart, R.C., dan J. Kennedy. “Particle Swarm Optimization”. Proceeding of the IEEEInternational Joint Conference on Neural Networks,
[8] Engelbrecht, Andries P. Fundamentals ofComputational Swarm Intelligence. Wiley.2005.
[9] Efendi, Rusdi. “Modifikasi Algoritma Particle Swarm Optimization untuk Pencarian Multi Sumber Gas: Simulasi dan Analisis”. Tesis FASILKOM, Universitas Indonesia. 2008.
[10] Nugraha, A., W. Jatmiko, dan J. Perkasa. “Modifikasi Particle Swarm Optimization untuk Pencarian Banyak Sumber Gas”. Jurnal Ilmu Komputer dan Informasi. Juli 2008.
[11] Jatmiko, W., Febrian, A., Jovan, F., Suryana, M.E., Insani, A. (2010). Swarm Robot dalam Pencarian Sumber Asap, UI Press.
[12] Hinze, J.O., Turbulance. McGraw-Hill, 1995.
[13] Wisnu Jatmiko, and Toshio Fukuda, and Takayuki Matsuno, and Fumihito Arai, and Benyamin Kusumoputro. (2005). Robotic Applications for Odor-Sensing Technology: Progress and Challenge. WSEAS TRANSACTIONS on SYSTEMS.
[14] Martinoli, Hayes, A., A.T., Goodman, R. M. (2002). Distributed odor source localization. IEEE Sensors.
[15] Martinoli, Hayes, A., A.T., Goodman, R. M. (2003). Swarm robotic odor localization: Off-line optimization and validation with real robots. Robotica.
[16] Belanger, J.H., Wilis, M.A. (1998). Biologically-inspired search algorithms for locating unseen odor sources. In Proceedings of the 1998 IEEE ISIS/CIRA/ISAS Joint Conference on the Science and Technology of Intelligent Systems.
[17] Engelbrecht Andries P. (2005). Fundamentals of Computational Swarm Intelligence. Wiley.
[18] Blackwell, T. M., Bentley, P. J. (2004). Dynamic search with charged swarms. In Proceedings of the Genetic and Evolutionary Computation Conference.
[19] Blackwell, T. M. (2002). Swarms in dynamic environment. In Proceedings of the Genetic and Evolutionary Computation.
[20] Blackwell, T. M., and Bentley, P. J. (2002). Dont push me! collision-avoiding swarms. In Proceedings of the IEEE Congress on Evolutionary Computation.
[21] F. W. Aribowo and I. Setiawan, -Penjejak ArahCahaya Dengan Kendali Logika, J. Tek. elektro, pp. 144–150, 2008.
[22] S. A. El-teleity, -Fuzzy Logic Control of an Autonomous MobileRobot, pp. 188–193, 2011.
[23] da S. Henrique V, C. K. Morooka, I. R. Guilherme, T. C. Fonseca, and J. R. P. Mendes, -Leak detection in petroleum pipelines using a fuzzy system, ELSEVIER, J. Pet. Sci. Eng., vol. 49, pp. 223–238, 2005.
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Copyright
© Computer Engineering and Applications Journal, 2017
Affiliations
Nyayu Latifah Husni
Politeknik Negeri Sriwijaya
Ade Silvia
Politeknik Negeri Sriwijaya
Siti Nurmaini
Universita Sriwijaya
Falah Yuridho
Politeknik Negeri Sriwijaya
Irsyadi Yani
Universita Sriwijaya
Swarm Robot Implementation in Gas Searching Using Particle Swarm Optimization Algorithm
Abstract
In this reseach, a PSO method is impelemented in searching a gas leakage. A swarm robot consisted of 3 agents, yelow, blue, and green, was used. The research was done in 2 type of experiments, i.e. in simulation and real expeiment. A Matlab is used as a simulation validation while for the real experiment, a 2 x 2 m arena is used. From the experiment, it can be concluded that a good performance of a swam can be achieved using PSO method.