A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles

© 2014 IEEE. One of the trademark behaviors of a swarm is aggregation. Aggregation is the ability to gather swarm members around a specific point in space. The goal is to keep an object, stationary or moving, at the center of the swarm. This paper presents a novel approach to centroid tracking in ro...

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Main Authors: Nakano, Reiichiro Christian S., Bandala, Argel A., Faelden, Gerard Ely, Maningo, Jose Martin Z., Dadios, Elmer Jose P.
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Published: Animo Repository 2014
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1497
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-24962022-05-13T05:01:48Z A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles Nakano, Reiichiro Christian S. Bandala, Argel A. Faelden, Gerard Ely Maningo, Jose Martin Z. Dadios, Elmer Jose P. © 2014 IEEE. One of the trademark behaviors of a swarm is aggregation. Aggregation is the ability to gather swarm members around a specific point in space. The goal is to keep an object, stationary or moving, at the center of the swarm. This paper presents a novel approach to centroid tracking in robotic swarms. Genetic algorithm is used in quadrotor unmanned aerial vehicles to keep the object being tracked at the center while minimizing two parameters: the distance travelled by each quadrotor and the distance of each quadrotor from the object. Centroid tracking was found to have an average error of 0.0623568 units for swarm populations ranging from 10 to 100 with the lower swarm populations exhibiting lower errors. Convergence did not exceed the maximum of 23 milliseconds for populations less than 30. These results show that the algorithm is well-suited for implementation in swarms with lower numbers of quadrotors. 2014-01-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1497 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2496/type/native/viewcontent Faculty Research Work Animo Repository
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description © 2014 IEEE. One of the trademark behaviors of a swarm is aggregation. Aggregation is the ability to gather swarm members around a specific point in space. The goal is to keep an object, stationary or moving, at the center of the swarm. This paper presents a novel approach to centroid tracking in robotic swarms. Genetic algorithm is used in quadrotor unmanned aerial vehicles to keep the object being tracked at the center while minimizing two parameters: the distance travelled by each quadrotor and the distance of each quadrotor from the object. Centroid tracking was found to have an average error of 0.0623568 units for swarm populations ranging from 10 to 100 with the lower swarm populations exhibiting lower errors. Convergence did not exceed the maximum of 23 milliseconds for populations less than 30. These results show that the algorithm is well-suited for implementation in swarms with lower numbers of quadrotors.
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author Nakano, Reiichiro Christian S.
Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin Z.
Dadios, Elmer Jose P.
spellingShingle Nakano, Reiichiro Christian S.
Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin Z.
Dadios, Elmer Jose P.
A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
author_facet Nakano, Reiichiro Christian S.
Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin Z.
Dadios, Elmer Jose P.
author_sort Nakano, Reiichiro Christian S.
title A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
title_short A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
title_full A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
title_fullStr A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
title_full_unstemmed A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
title_sort genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles
publisher Animo Repository
publishDate 2014
url https://animorepository.dlsu.edu.ph/faculty_research/1497
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2496/type/native/viewcontent
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