Obstacle avoidance in mobile robots in RGB-D images using deep neural network and semantic segmentation

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dc.contributor.authorAl-Adhami, Abdulrahman Abdulwahab Kaml
dc.contributor.authorCansever, Galip
dc.date.accessioned2022-08-08T13:19:43Z
dc.date.available2022-08-08T13:19:43Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractAutomating industrial and commercial activities through the use of manipulative robots capable of movement and carrying a variety of products is gaining popularity. When it comes to mobile robots, their operating systems are more complex, which means they are more in demand due to their use in research, which increases their price. These devices run on a variety of operating systems. Obstacle avoidance, line tracking, and mobile explorers are just a few examples. As a result of our findings, we propose a vision system that utilizes a feature extraction and classification algorithm DNN for obstacles in RGB-D images in order to detect and avoid obstacles in known environments.en_US
dc.identifier.citationAL-adhami, A. A. K., Cansever, G. (2022). Obstacle avoidance in mobile robots in RGB-D images using deep neural network and semantic segmentation. In 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), IEEE.en_US
dc.identifier.isbn9781665468350
dc.identifier.scopus2-s2.0-85133966144
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12939/2807
dc.indekslendigikaynakScopus
dc.institutionauthorAl-Adhami, Abdulrahman Abdulwahab Kaml
dc.institutionauthorCansever, Galip
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofHORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings
dc.relation.isversionof10.1109/HORA55278.2022.9800030en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCNNen_US
dc.subjectDLen_US
dc.subjectMLen_US
dc.subjectRGB-Den_US
dc.subjectRoboticsen_US
dc.subjectSVMen_US
dc.titleObstacle avoidance in mobile robots in RGB-D images using deep neural network and semantic segmentation
dc.typeConference Object

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