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http://dx.doi.org/10.12673/jant.2017.21.5.443

Consensus-based Autonomous Search Algorithm Applied for Swarm of UAVs  

Park, Kuk-Kwon (Department of Aerospace Engineering, Inha University)
Kwon, Ho-Jun (Department of Aerospace Engineering, Inha University)
Choi, Eunju (Department of Aerospace Engineering, Inha University)
Ryoo, Chang-Kyung (Department of Aerospace Engineering, Inha University)
Publication Information
Journal of Advanced Navigation Technology / v.21, no.5, 2017 , pp. 443-449 More about this Journal
Abstract
Swarm of low-cost UAVs for search mission has benefit in the sense of rapid search compared to use of single high-end UAV. As the number of UAVs forming swarm increases, not only the time for the mission planning increases, but also the system to operate UAVs has excessive burden. This paper addresses a decentralized area search algorithm adequate for multiple UAVs which takes advantages of flexibility, robustness, and simplicity. To down the cost, it is assumed that each UAV has limited ability: close-communication, basic calculation, and limited memory. In close-communication, heath conditions and search information are shared. And collision avoidance and consensus of next search direction are then done. To increase weight on un-searched area and to provide overlapped search, the score function is introduced. Performance and operational characteristics of the proposed search algorithm and mission planning logic are verified via numerical simulations.
Keywords
Unmanned aerial vehicles; Swarm; Area search; Autonomous; Collision avoidance;
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  • Reference
1 E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence : from Natural to Artificial Systems, Oxford University Press, 1999.
2 J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proceedings of the IEEE International Conference on Neural Networks, Piscataway, pp.1942-1948, 1995.
3 M. Dorigo and T. Stutzle, Ant Colony Optimization, MIT Press, 2004.
4 C. A. Erignac, "An exhaustive swarming search strategy based on distributed pheromone maps," in AIAA Infotech@Aerospace 2007 Conference and Exhibit, California, 2007.
5 E. Kuiper, and S. Nadjm-Tehrani, "Mobility models for UAV group reconnaissance applications," in Proceedings of the International Conference on Wireless and Mobile Communications, Romania, pp. 33-38, 2006.
6 R. Parasuraman, T. B. Sheridan, and C. D. Wickens, "A model for types and levels of human interaction," IEEE Transactions on Systems, Man, and Cybernetics, Systems and humans, Vol.30, No. 3, 2000.