Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
IEEE International Conference on Intelligent Robots and Systems
Volume
2016-November
First Page
1715
Last Page
1720
Publication Date
11-28-2016
Abstract
© 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.
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Digitial Object Identifier (DOI)
10.1109/IROS.2016.7759275
Recommended Citation
Bandala, A. A., Faelden, G., Maningo, J., Nakano, R. S., Vicerra, R. P., & Dadios, E. P. (2016). Implementation of varied particle container for smoothed particle hydrodynamics - Based aggregation for unmanned aerial vehicle quadrotor swarm. IEEE International Conference on Intelligent Robots and Systems, 2016-November, 1715-1720. https://doi.org/10.1109/IROS.2016.7759275
Disciplines
Electrical and Computer Engineering | Electrical and Electronics
Keywords
Multiagent systems; Drone aircraft; Robots
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