Mоlimо vаs kоristitе оvај idеntifikаtоr zа citirаnjе ili оvај link dо оvе stаvkе:
https://open.uns.ac.rs/handle/123456789/8554
Nаziv: | PSO and GA optimization methods comparison on simulation model of a real hexapod robot | Аutоri: | Kecskés I. Székács L. Fodor J. Odry P. |
Dаtum izdаvаnjа: | 8-нов-2013 | Čаsоpis: | ICCC 2013 - IEEE 9th International Conference on Computational Cybernetics, Proceedings | Sažetak: | The Szabad(ka)-II hexapod robot with 18 DOF is a suitable mechatronic device for the development of hexapod walking algorithm and engine control [1, 2]. The required full dynamic model has already been built [3], which is used as a black-box for the walking optimizations in this research. The ellipse-based walking trajectory has been generated that was required by the low-cost straight line walking [4], and the purpose was to optimize its parameters. The Particle Swarm Optimization (PSO) method was chosen for simple and effective working, which does not require the model's mathematical description or differentiation. Previously the authors performed an evolutionary Genetic Algorithm (GA) optimization for a similar trial case [5], and posed the principles of the quality measurement of hexapod walking [4, 5]. The same visual evaluation and comparison was applied in this paper for the results of both optimization methods. PSO has produced better and faster results compared to GA. © 2013 IEEE. | URI: | https://open.uns.ac.rs/handle/123456789/8554 | ISBN: | 9781479900633 | DOI: | 10.1109/ICCCyb.2013.6617574 |
Nаlаzi sе u kоlеkciјаmа: | Naučne i umetničke publikacije |
Prikаzаti cеlоkupаn zаpis stаvki
SCOPUSTM
Nаvоđеnjа
32
prоvеrеnо 10.05.2024.
Prеglеd/i stаnicа
13
Prоtеklа nеdеljа
8
8
Prоtеkli mеsеc
0
0
prоvеrеnо 10.05.2024.
Google ScholarTM
Prоvеritе
Аlt mеtrikа
Stаvkе nа DSpace-u su zаštićеnе аutоrskim prаvimа, sа svim prаvimа zаdržаnim, оsim аkо nije drugačije naznačeno.