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dc.contributor.authorAlshanbari, Reem
dc.contributor.authorKhan, Sherjeel M.
dc.contributor.authorElatab, Nazek
dc.contributor.authorHussain, Muhammad Mustafa
dc.date.accessioned2020-04-27T10:35:36Z
dc.date.available2020-04-27T10:35:36Z
dc.date.issued2020-04-10
dc.identifier.citationAlshanbari, R., Khan, S., El-Atab, N., & Mustafa Hussain, M. (2019). AI Powered Unmanned Aerial Vehicle for Payload Transport Application. 2019 IEEE National Aerospace and Electronics Conference (NAECON). doi:10.1109/naecon46414.2019.9058320
dc.identifier.isbn9781728114163
dc.identifier.issn2379-2027
dc.identifier.issn0547-3578
dc.identifier.doi10.1109/NAECON46414.2019.9058320
dc.identifier.urihttp://hdl.handle.net/10754/662656
dc.description.abstractRecently unmanned aerial vehicles (UAV) have received a growing attention due to their wide range of applications. Here, we demonstrate UAVs with artificial intelligence (AI) capabilities for application in autonomous payload transport. An algorithm is developed for target detection with multiple phases on the ground, which once the target is detected, would trigger the release of the payload that is attached on the drone. The experimental results show that the average frame rate over x seconds achieved a 19.4010717352 fps (frame per second) detection speed. Releasing the payload is achieved using a 3D printed system based on rack and pinion gears. In addition, auto flight program is developed to enable the autonomous movement of the drone. As a proof-of-concept, a small drone known as "Phantom DJI" is used for.6 kg autonomous payload transport along a predefined route to a target location.
dc.description.sponsorshipThe work is supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. Sensor Innovation Initiative OSR-2015-Sensors-2707 and KAUST-KFUPM Special Initiative OSR-2016-KKI-2880
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9058320/
dc.rightsArchived with thanks to IEEE
dc.titleAI Powered Unmanned Aerial Vehicle for Payload Transport Application
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentIntegrated Nanotechnology Lab
dc.contributor.departmentKing Abdullah University of Science and Technology,mmh Labs, Computer, Elecctrical and Mathematical Sciences and Engineering Division,Thuwal,Saudi Arabia
dc.conference.date2019-07-15 to 2019-07-19
dc.conference.name2019 IEEE National Aerospace and Electronics Conference, NAECON 2019
dc.conference.locationDayton, OH, USA
dc.eprint.versionPost-print
dc.contributor.institutionElecctrical Engineering and Computer Science, University of California, Berkeley, California, USA
dc.identifier.volume2019-July
dc.identifier.pages420-424
kaust.personAlshanbari, Reem
kaust.personKhan, Sherjeel
kaust.personElatab, Nazek
kaust.personHussain, Muhammad Mustafa
kaust.grant.numberOSR-2015-Sensors-2707
kaust.grant.numberOSR-2016-KKI-2880
dc.identifier.eid2-s2.0-85083297168
refterms.dateFOA2020-04-28T06:47:03Z
kaust.acknowledged.supportUnitKAUST-KFUPM Special Initiative
kaust.acknowledged.supportUnitOffice of Sponsored Research (OSR)
kaust.acknowledged.supportUnitSensor Innovation Initiative


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