Car-like robot path planning based on voronoi and Q-learning algorithms

Basit Öğe Kaydı
dc.authorid0000-0003-4511-7694en_US
dc.authorid0000-0002-4249-6951en_US
dc.contributor.authorAlhassow, Mustafa Mohammed
dc.contributor.authorAta, Oğuz
dc.contributor.authorAtilla, Doğu Çağdaş
dc.date.accessioned2022-03-08T06:20:10Z
dc.date.available2022-03-08T06:20:10Z
dc.date.issued2021en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThis paper discusses a differential path planning issue for the mobile robot depending on Voronoi diagram (VD) and Q-learning algorithms (QL). The issues with re-arranging paths in a dynamic environment with obstructions are treated as an issue of looking for the best route between the start and target stage. Since the car-like robot is differentially system and its mathematically involved with the inward state of impediment because of that some modification will be embedded like the orientation method. This is a unique instance of a solitary vehicle, which just goes ahead at a consistent speed and can just turn left also, right. Voronoi diagram presents the world encompassing brilliant specialists for robots, computer games, and military issues, so improving the dependability, of arranging the environment using it will help and decrease Q learning calculations by re-updating the Q-table, according to the new state, also decreasing both existence intricacy, relies upon earlier information that came from the environment. The work arrangement was tested for a 2D environment. The result of the proposed work showed better performance in time, speed, and length of the path also it can be utilized as an alternate style of guides. A comparison with other related works is performed and the result of these comparisons showed that our work provides a good trajectory with performance.en_US
dc.identifier.citationAlhassow, M. M., Ata, O., & Atilla, D. C. (2021, October). Car-Like Robot Path Planning Based on Voronoi and Q-Learning Algorithms. In 2021 International Conference on Engineering and Emerging Technologies (ICEET) (pp. 1-4). IEEE.en_US
dc.identifier.endpage4en_US
dc.identifier.scopus2-s2.0-85124648374
dc.identifier.scopusqualityN/A
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/2270
dc.identifier.wosWOS:000828108100104
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAlhassow, Mustafa Mohammed
dc.institutionauthorAta, Oğuz
dc.institutionauthorAtilla, Doğu Çağdaş
dc.language.isoen
dc.publisherICEETen_US
dc.relation.ispartofIEEE
dc.relation.isversionof10.1109/ICEET53442.2021.9659777en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCar-Like Roboten_US
dc.subjectNonholonomic Systemen_US
dc.subjectPath Planningen_US
dc.subjectQ-Learningen_US
dc.subjectVoronoi Diagramen_US
dc.titleCar-like robot path planning based on voronoi and Q-learning algorithms
dc.typeArticle

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
Bilgisayar Mühendisliği Bölümü Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu