Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm

© 2016 IEEE. The property of the Smoothed Particle Hydrodynamies(SPH) method of being mesh free, adaptable and suitable for tracking of individual particles makes it appropriate for approximating swarm behaviors for multiagent robotics applications. The researchers modeled each of the swarm robots a...

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Main Authors: Bandala, Argel A., Faelden, Gerard Ely, Maningo, Jose Martin, Nakano, Reiichiro Christian S., Vicerra, Ryan Rhay P., Dadios, Elmer P.
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Published: Animo Repository 2016
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3631
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4633/type/native/viewcontent/IROS.2016.7759275
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-46332021-09-20T06:33:13Z Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm Bandala, Argel A. Faelden, Gerard Ely Maningo, Jose Martin Nakano, Reiichiro Christian S. Vicerra, Ryan Rhay P. Dadios, Elmer P. © 2016 IEEE. The property of the Smoothed Particle Hydrodynamies(SPH) method of being mesh free, adaptable and suitable for tracking of individual particles makes it appropriate for approximating swarm behaviors for multiagent robotics applications. The researchers modeled each of the swarm robots as SPH particles and then subjected them to external forces to exhibit aggregation and force certain formations. The external forces subjected to the SPH particles are gravity forces and container constraints. The containers explored in the study are si mple geometrical prim itives: sphere and cube.Computer simulations were done to show how SPH can facilitate in forcing swarm formations with the help of bounding primitives. Algorithm benchmarking was done to show how well SPH pe rforms. Results show thatSPH performs better than the benchmark algorithm by a margin of 0.703 and 1.016 units for the two set-ups, respectively. Actual robot implementation was also done to verify the effectivity and viability of the proposed algorithm in exhibiting the aggregation be havior. After 15 seconds of system ru n ti me, the interparticle distance and motion accuracy reached 96.93% and 91.14%, respectively. 2016-11-28T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/3631 info:doi/10.1109/IROS.2016.7759275 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4633/type/native/viewcontent/IROS.2016.7759275 Faculty Research Work Animo Repository Multiagent systems Drone aircraft Robots Electrical and Computer Engineering Electrical and Electronics
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Multiagent systems
Drone aircraft
Robots
Electrical and Computer Engineering
Electrical and Electronics
spellingShingle Multiagent systems
Drone aircraft
Robots
Electrical and Computer Engineering
Electrical and Electronics
Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin
Nakano, Reiichiro Christian S.
Vicerra, Ryan Rhay P.
Dadios, Elmer P.
Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
description © 2016 IEEE. The property of the Smoothed Particle Hydrodynamies(SPH) method of being mesh free, adaptable and suitable for tracking of individual particles makes it appropriate for approximating swarm behaviors for multiagent robotics applications. The researchers modeled each of the swarm robots as SPH particles and then subjected them to external forces to exhibit aggregation and force certain formations. The external forces subjected to the SPH particles are gravity forces and container constraints. The containers explored in the study are si mple geometrical prim itives: sphere and cube.Computer simulations were done to show how SPH can facilitate in forcing swarm formations with the help of bounding primitives. Algorithm benchmarking was done to show how well SPH pe rforms. Results show thatSPH performs better than the benchmark algorithm by a margin of 0.703 and 1.016 units for the two set-ups, respectively. Actual robot implementation was also done to verify the effectivity and viability of the proposed algorithm in exhibiting the aggregation be havior. After 15 seconds of system ru n ti me, the interparticle distance and motion accuracy reached 96.93% and 91.14%, respectively.
format text
author Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin
Nakano, Reiichiro Christian S.
Vicerra, Ryan Rhay P.
Dadios, Elmer P.
author_facet Bandala, Argel A.
Faelden, Gerard Ely
Maningo, Jose Martin
Nakano, Reiichiro Christian S.
Vicerra, Ryan Rhay P.
Dadios, Elmer P.
author_sort Bandala, Argel A.
title Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
title_short Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
title_full Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
title_fullStr Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
title_full_unstemmed Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
title_sort implementation of varied particle container for smoothed particle hydrodynamics - based aggregation for unmanned aerial vehicle quadrotor swarm
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/faculty_research/3631
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4633/type/native/viewcontent/IROS.2016.7759275
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