Gas Source Localization using Grey Wolf Optimizer

Authors

  • S.M. Mamduh Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mikroelektronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • K. Kamarudin Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mekatronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • A.Y.M. Shakaff Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mekatronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • A. Zakaria Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mekatronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • R. Visvanathan Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mekatronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • A.S.A. Yeon Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Mekatronik, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • L.M. Kamarudin Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600. Pusat Pengajian Kejuruteraan Komputer dan Perhubungan, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600.
  • A.S.A. Nasir Fakulti Teknologi Kejuruteraan, Universiti Malaysia Perlis (UniMAP), Padang Besar, Perlis 02100.

Keywords:

Gas Source Localization, Grey Wolf Optimizer, Mobile Olfaction, Swarm Intelligence,

Abstract

Gas source localization is an ability which has yet to be successfully implemented in synthetic systems although it is widely exhibited by various organisms. Although single robot implementation has been explored, it is still prone to single point failures and is limited in sporadic gas dispersion conditions. Swarm intelligence based algorithms such as Particle Swarm Optimization and Ant Colony Optimization has shown the feasibility and advantage of using multi-robot strategy for gas source localization. This paper explores Grey Wolf Optimizer (GWO) as an alternative algorithm for gas source localization. It was found that, although some GWO search behavior is favorable for gas source localization, the algorithm may fail when used with low numbers of robots. The algorithm was able to localize the peak gas concentration in approximately 30 minutes. The best success rate is found to be 72% with 7 searcher robots.

References

Fraenkel, G.S. and D.L. Gunn, The orientation of animals, kineses, taxes and compass reactions. 1961: Dover Publications.

Kamarudin, K., et al., “Flexible and Autonomous Integrated System for Characterizing Metal Oxide Gas Sensor Response in Dynamic Environment,” Instrumentation Science & Technology, vol. 43(1), 2015.: pp. 74-88.

Mamduh, S., et al., Comparison of Braitenberg Vehicles with BioInspired Algorithms for Odor Tracking in Laminar Flow. Australian Journal of Basic & Applied Sciences, vol 8(4). 2014.

Mamduh, S.M., et al., “Braitenberg swarm vehicles for odour plume tracking in laminar airflow,” IEEE Symposium on Computers & Informatics (ISCI), 2013.

Marjovi, A. and L. Marques, “Swarm robotic plume tracking for intermittent and time-variant odor dispersion,” 2013 European Conference on Mobile Robots (ECMR), 2013.

Marjovi, A. and L. Marques, “Multi-robot odor distribution mapping in realistic time-variant conditions,” 2014 IEEE International Conference on in Robotics and Automation (ICRA), 2014.

Marjovi, A. and L. Marques, “Optimal spatial formation of swarm robotic gas sensors in odor plume finding,” Autonomous Robots, vol 35(2-3), 2013, pp. 93-109.

Kennedy, J. and R. Eberhart. “Particle swarm optimization,” IEEE International Conference on Neural Networks, 1995.

Marques, L. and A.T. de Almeida, “Finding Odours Across Large Search Spaces: A Particle Swarm-Based Approach,” in Climbing and Walking Robots, Springer Berlin Heidelberg, 2005, p. 419-426.

Marques, L., U. Nunes, and A.T. de Almeida, “Particle swarm-based olfactory guided search,” Autonomous Robots, vol. 20(3), 2006. pp. 277-287.

Akat, S.B., V. Gazi, and L. Marques, “Asynchronous particle swarm optimization-based search with a multi-robot system: simulation and implementation on a real robotic system,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 18(5), 2010. pp. 749-764.

Ferri, G., et al., “Explorative Particle Swarm Optimization method for gas/odor source localization in an indoor environment with no strong airflow,” IEEE International Conference on Robotics and Biomimetics, 2007.

Dorigo, M., V. Maniezzo, and A. Colorni, “Ant system: optimization by a colony of cooperating agents,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 26(1), 1996, pp. 29- 41.

Yuhua, Z., L. Dehan, and C. Weihai. “Swarm robotic odor source localization using ant colony algorithm,” IEEE International Conference on Control and Automation, 2009.

Mirjalili, S., S.M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, 2014. pp. 46-61.

Kamboj, V.K., “A novel hybrid PSO–GWO approach for unit commitment problem,” Neural Computing and Applications, 2015, pp. 1-13.

Komaki, G.M. and V. Kayvanfar, “Grey Wolf Optimizer algorithm for the two-stage assembly flow shop scheduling problem with release time,” Journal of Computational Science, vol. 9, 2015, pp. 109-120.

Mirjalili, S., “How effective is the Grey Wolf optimizer in training multi-layer perceptrons,” Applied Intelligence, vol. 43(1), 2015, pp. 150-161.

Syed Zakaria, S., et al., “Development of a Scalable Testbed for Mobile Olfaction Verification,” Sensors, vol. 15(12), 2015, pp. 29834.

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Published

2018-05-29

How to Cite

Mamduh, S., Kamarudin, K., Shakaff, A., Zakaria, A., Visvanathan, R., Yeon, A., Kamarudin, L., & Nasir, A. (2018). Gas Source Localization using Grey Wolf Optimizer. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-13), 95–98. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4130

Issue

Vol. 10 No. 1-13: Exploring Man-Machines Compliance in Signal Processing and Artificial Intelligence

Section

Articles

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