Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8647
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKarahan M.-
dc.contributor.authorKasnakoğlu, Coşku-
dc.date.accessioned2022-07-30T16:43:42Z-
dc.date.available2022-07-30T16:43:42Z-
dc.date.issued2021-
dc.identifier.citationKarahan, M., & Kasnakoglu, C. Path Planning and Collision Avoidance with Artificial Intelligence for a Quadrotor UAV. In 2021 International Conference Automatics and Informatics (ICAI) (pp. 163-166). IEEE.en_US
dc.identifier.isbn9781665426619-
dc.identifier.urihttps://doi.org/10.1109/ICAI52893.2021.9639807-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/8647-
dc.description2021 International Conference Automatics and Informatics, ICAI 2021 -- 30 September 2021 through 2 October 2021 -- -- 175600en_US
dc.description.abstractArtificial intelligence has brought new features to unmanned aerial vehicles. Path planning, trajectory optimization and obstacle avoidance are some of the features that artificial intelligence brings to drones. In this study, path planning optimization and collision avoidance with artificial intelligence for an unmanned aerial vehicle are emphasized. Path planning and collision avoidance simulations were performed using MATLAB software under ideal conditions and under noisy conditions. It is shown that the unmanned aerial vehicle finds the shortest path on maps with various obstacles. © 2021 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofInternational Conference Automatics and Informatics, ICAI 2021 Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectA-star algorithmen_US
dc.subjectartificial intelligenceen_US
dc.subjectobstacle avoidanceen_US
dc.subjectoptimizationen_US
dc.subjectpath planningen_US
dc.subjectQuadrotoren_US
dc.subjectUAVen_US
dc.subjectAntennasen_US
dc.subjectCollision avoidanceen_US
dc.subjectMATLABen_US
dc.subjectMotion planningen_US
dc.subjectA-Star algorithmen_US
dc.subjectCollisions avoidanceen_US
dc.subjectConditionen_US
dc.subjectNoisy conditionsen_US
dc.subjectObstacles avoidanceen_US
dc.subjectOptimisationsen_US
dc.subjectQuad rotorsen_US
dc.subjectShort-pathen_US
dc.subjectTrajectory optimizationen_US
dc.subjectUnmanned aerial vehicles (UAV)en_US
dc.titlePath Planning and Collision Avoidance with Artificial Intelligence for a Quadrotor UAVen_US
dc.typeConference Objecten_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.identifier.startpage163en_US
dc.identifier.endpage166en_US
dc.identifier.scopus2-s2.0-85123858097en_US
dc.institutionauthorKasnakoğlu, Coşku-
dc.identifier.doi10.1109/ICAI52893.2021.9639807-
dc.authorscopusid57216759940-
dc.authorscopusid24802064500-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Object-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Apr 20, 2024

Page view(s)

108
checked on Apr 15, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.