Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Optimization of physical parameters of an underactuated quadrupedal robot
Date
2018-01-01
Author
Karagoz, Osman Kaan
Ankaralı, Mustafa Mert
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
232
views
0
downloads
Cite This
In this paper, we present the comparison of different optimization algorithms that are used to optimize the parameters of a simulated legged robotic platform. We compare the results obtained by applying different algorithms on the same model and show the relative advantages and disadvantages of these algorithms. The tested algorithms are Particle Swarm Optimization, Binary Coded Genetic Algorithm, Broyden-Fletcher-Goldfrab-Shannon Algorithm and Method of Zoutendijk. We showed that the globally optimal parameter set reduces the total dissipated energy approximately 50% with respect to the reference paremeter set in the literature. The implemented optimization methods can also be applied to other legged platforms to obtain efficient systems without affecting the performance and the stability.
Subject Keywords
Binary coded genetic algorithm
,
Method of Zoutendijk
,
Broyden-Fletcher-Goldfrab-Shannon algorithm
,
Legged robot
URI
https://hdl.handle.net/11511/38419
DOI
https://doi.org/10.1109/siu.2018.8404581
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Comparison of Facial Alignment Techniques: With Test Results on Gender Classification Task
Kaya, Tunç Güven (2014-08-24)
In this paper, different facial alignment techniques are revised in terms of their effects on machine learning algorithms. This paper, investigates techniques that are widely accepted in literature and measures their effect on gender classification task. There is no special reason on selecting gender classification task, any other task could have been chosen. In audience measurement systems, many important demographics, i.e. gender, age, facial expression, can be measured by using machine learning algorithm...
Efficient and Accurate Electromagnetic Optimizations Based on Approximate Forms of the Multilevel Fast Multipole Algorithm
Onol, Can; Karaosmanoglu, Bariscan; Ergül, Özgür Salih (2016-01-01)
We present electromagnetic optimizations by heuristic algorithms supported by approximate forms of the multilevel fast multipole algorithm (MLFMA). Optimizations of complex structures, such as antennas, are performed by considering each trial as an electromagnetic problem that can be analyzed via MLFMA and its approximate forms. A dynamic accuracy control is utilized in order to increase the efficiency of optimizations. Specifically, in the proposed scheme, the accuracy is used as a parameter of the optimiz...
Optimizations of antennas using heuristic algorithms supported by the multilevel fast multipole algorithm
Önol, Can; Ergül, Özgür Salih; Department of Electrical and Electronics Engineering (2015)
In this study, an optimization environment based on heuristic algorithms supported by the multilevel fast multipole algorithm (MLFMA) is presented for different antenna problems involving either excitation or geometry optimizations. The heuristic algorithms are implemented in-house by aiming more effective interactions between electromagnetic solvers and optimization algorithms, instead of black box interactions. Excitation optimizations of various array geometries for desired radiation characteristics are ...
Computational design of nanoantennas with improved power enhancement capabilities via shape optimization
Işiklar, Göktuǧ; Yazar, Şirin; İbili, Hande; Onay, Gülten; El Ahdab, Zeina; Ergül, Özgür Salih (2023-01-01)
Computational design and analyses of nanoantennas obtained via surface shape optimization are presented. Starting with a kernel geometry, free deformations are applied on selected surfaces to reach optimal designs that can provide improved power enhancement capabilities at desired frequencies. An in-house implementation of genetic algorithms is efficiently combined with the multilevel fast multipole algorithm developed for accurate solutions of plasmonic problems to construct the effective optimization envi...
Optimizations of Patch Antenna Arrays Using Genetic Algorithms Supported by the Multilevel Fast Multipole Algorithm
Onol, Can; Ergül, Özgür Salih (2014-12-01)
We present optimizations of patch antenna arrays using genetic algorithms and highly accurate full-wave solutions of the corresponding radiation problems with the multilevel fast multipole algorithm (MLFMA). Arrays of finite extent are analyzed by using MLFMA, which accounts for all mutual couplings between array elements efficiently and accurately. Using the superposition principle, the number of solutions required for the optimization of an array is reduced to the number of array elements, without resorti...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. K. Karagoz and M. M. Ankaralı, “Optimization of physical parameters of an underactuated quadrupedal robot,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38419.