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Visualization of deep reinforcement autonomous aerial mobility learning simulationsoa mark
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Publication Year
2021-05-10
Journal
IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
Mesh Keyword
3D VisualizationLearning simulationUrban environments
All Science Classification Codes (ASJC)
Artificial IntelligenceComputer Networks and CommunicationsHardware and ArchitectureInformation Systems and ManagementSafety, Risk, Reliability and Quality
Abstract
This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is used and additional buildings are introduced for urban environment. On top of the implementation, DRL algorithms are used and we confirm it works well in terms of trajectory and 3D visualization.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36708
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85113332011&origin=inward
DOI
https://doi.org/10.1109/infocomwkshps51825.2021.9484462
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9484327
Type
Conference
Funding
ACKNOWLEDGMENT This research is supported by National Research Foundation of Korea (2019R1A2C4070663 and 2019M3E4A1080391). S. Jung, J. Kim, and J.-H. Kim are corresponding authors.
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Jung, Soyi Image
Jung, Soyi정소이
Department of Electrical and Computer Engineering
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