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Deep Reinforcement Learning-based Optimal Takeoff Trajectory Design of an eVTOL Drone

  • Missouri University of Science and Technology
  • California State University Fullerton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationAIAA AVIATION FORUM AND ASCEND, 2025
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107382
DOIs
StatePublished - 2025
EventAIAA AVIATION FORUM AND ASCEND, 2025 - Las Vegas, United States
Duration: Jul 21 2025Jul 25 2025

Publication series

NameAIAA Aviation Forum and ASCEND, 2025

Conference

ConferenceAIAA AVIATION FORUM AND ASCEND, 2025
Country/TerritoryUnited States
CityLas Vegas
Period7/21/257/25/25

ASJC Scopus Subject Areas

  • Space and Planetary Science
  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Aerospace Engineering

Keywords

  • Airbus
  • Drone
  • Electric Vertical Take off and Landing
  • Energy Consumption
  • Lift Coefficient
  • Mathematical Models
  • Multidisciplinary Design and Optimization
  • Reinforcement Learning
  • Trajectory Design
  • Trajectory Optimization

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