Development of Deep Learning Algorithm for Humanoid Robots to Walk to the Target Using Semantic Segmentation and Deep Q Network

dc.contributor.authorAslan, Simge Nur
dc.contributor.authorUcar, Aysegul
dc.contributor.authorGuzelis, Cuneyt
dc.date.accessioned2026-08-12T16:08:34Z
dc.date.issued2020
dc.departmentFırat Üniversitesi
dc.description2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 -- 15 October 2020 through 17 October 2020 -- Istanbul -- 165305
dc.description.abstractIn this article, a new algorithm incorporating deep semantic segmentation algorithm and deep reinforcement algorithm is proposed to avoid the obstacle. This work was generated from two parts. The first part included semantic segmentation by using mini-Unet. The objects were detected and recognized. In the second part, Deep Q Network (DQN) was used for humanoid robots to learn to walk to target. The obtained results showed that the performance of proposed algorithm confirmed. © 2020 IEEE.
dc.identifier.doi10.1109/ASYU50717.2020.9259888
dc.identifier.isbn978-172819136-2
dc.identifier.scopus2-s2.0-85097934900
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ASYU50717.2020.9259888
dc.identifier.urihttps://hdl.handle.net/11508/41300
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings - 2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectdeep Q network; deep reinfrocement learnig; humanoid robots; semantic segmentation
dc.titleDevelopment of Deep Learning Algorithm for Humanoid Robots to Walk to the Target Using Semantic Segmentation and Deep Q Network
dc.title.alternativeAnlamsal Bölütleme ve Derin Q Agi Kullanarak Hedefe Do?ru Yürümek Için Yeni Bir Derin Ö?renme Algoritmasinin Geliştirilmesi
dc.typeConference Object

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