Swarming algorithm for unmanned aerial vehicle (UAV) quadrotors - Swarm behavior for aggregation, foraging, formation, and tracking
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Article
Source Title
Journal of Advanced Computational Intelligence and Intelligent Informatics
Volume
18
Issue
5
First Page
745
Last Page
751
Publication Date
9-1-2014
Abstract
This paper presents the fusion of swarm behavior in multi robotic system specifically the quadrotors unmanned aerial vehicle (QUAV) operations. This study directed on using robot swarms because of its key feature of decentralized processing amongst its member. This characteristic leads to advantages of robot operations because an individual robot failure will not affect the group performance. The algorithm emulating the animal or insect swarm behaviors is presented in this paper and implemented into an artificial robotic agent (QUAV) in computer simulations. The simulation results concluded that for increasing number of QUAV the aggregation accuracy increases with an accuracy of 90.62%. The experiment for foraging revealed that the number of QUAV does not affect the accuracy of the swarm instead the iterations needed are greatly improved with an average of 160.53 iterations from 50 to 500 QUAV. For swarm tracking, the average accuracy is 89.23%. The accuracy of the swarm formation is 84.65%. These results clearly defined that the swarm system is accurate enough to perform the tasks and robust in any QUAV number. © 2014, Fuji Technology Press. All rights reserved.
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Digitial Object Identifier (DOI)
10.20965/jaciii.2014.p0745
Recommended Citation
Bandala, A. A., Dadios, E. P., Vicerra, R. P., & Gan Lim, L. A. (2014). Swarming algorithm for unmanned aerial vehicle (UAV) quadrotors - Swarm behavior for aggregation, foraging, formation, and tracking. Journal of Advanced Computational Intelligence and Intelligent Informatics, 18 (5), 745-751. https://doi.org/10.20965/jaciii.2014.p0745
Disciplines
Electrical and Electronics | Robotics
Keywords
Swarm intelligence; Drone aircraft
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