Control humanoid robot using intelligent optimization algorithms fusion with fourier series

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dc.contributor.authorAbedi, Erfan
dc.contributor.authorAlamirpour, Pooya
dc.contributor.authorMirshahvalad, Roxana
dc.date.accessioned2026-02-06T17:54:34Z
dc.date.issued2017
dc.departmentDoğu Akdeniz Üniversitesi
dc.description9th International Conference on Computational Intelligence and Communication Networks, CICN 2017 -- 2017-09-16 through 2017-09-17 -- Girne -- 135332
dc.description.abstractRobot walking on two feet is a complex motion. Researchers are trying to improve biped robots walking in case of walking speed. The analysis of biped walking patterns is used to obtain more detailed information in this field. Several researches have been done to achieve this purpose and the equation of walking trajectory is one of them. This article will introduce a new algorithm in which an evolutionary computing, based on learning automata along with a continual action on control signals of humanoid robot's motion, showing the success of the proposed method as the result to be used for optimizing the parameters of Truncated Fourier Series (TFS) after being compared with the results of Genetic Algorithm (GA) implementation. It is notable that the conditions of the experiment for these two algorithms are considered to be identical. © 2017 IEEE.
dc.identifier.doi10.1109/CICN.2017.8319381
dc.identifier.endpage185
dc.identifier.isbn9781509050017
dc.identifier.scopus2-s2.0-85050744581
dc.identifier.scopusqualityN/A
dc.identifier.startpage181
dc.identifier.urihttps://doi.org/10.1109/CICN.2017.8319381
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/
dc.identifier.urihttps://hdl.handle.net/11129/7449
dc.identifier.volume2018-January
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260204
dc.subjectbipedal locomotion
dc.subjectgenetic algorithm
dc.subjecthumnaoid robots
dc.subjectlearning automata
dc.subjecttruncated fourier series
dc.subjectwalking speed
dc.subjectwalking stability
dc.titleControl humanoid robot using intelligent optimization algorithms fusion with fourier series
dc.typeConference Object

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