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    AI Powered Unmanned Aerial Vehicle for Payload Transport Application

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    PID6083109.pdf
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    Description:
    Accepted manuscript
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    Type
    Conference Paper
    Authors
    Alshanbari, Reem
    Khan, Sherjeel M. cc
    Elatab, Nazek cc
    Hussain, Muhammad Mustafa cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering
    Electrical Engineering Program
    Integrated Nanotechnology Lab
    King Abdullah University of Science and Technology,mmh Labs, Computer, Elecctrical and Mathematical Sciences and Engineering Division,Thuwal,Saudi Arabia
    KAUST Grant Number
    OSR-2015-Sensors-2707
    OSR-2016-KKI-2880
    Date
    2020-04-10
    Permanent link to this record
    http://hdl.handle.net/10754/662656
    
    Metadata
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    Abstract
    Recently 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.
    Citation
    Alshanbari, 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
    Sponsors
    The 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
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Conference/Event name
    2019 IEEE National Aerospace and Electronics Conference, NAECON 2019
    ISBN
    9781728114163
    DOI
    10.1109/NAECON46414.2019.9058320
    Additional Links
    https://ieeexplore.ieee.org/document/9058320/
    ae974a485f413a2113503eed53cd6c53
    10.1109/NAECON46414.2019.9058320
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Integrated Nanotechnology Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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