Energy-Optimal Trajectory Planning for Near-Space Solar-Powered UAV Based on Hierarchical Reinforcement Learning

Energy-Optimal Trajectory Planning for Near-Space Solar-Powered UAV Based on Hierarchical Reinforcement Learning

One of the key technologies for achieving day and night flight, tracking solar peak, and reducing flight energy consumption for a near-space solar-powered unmanned aerial vehicle (UAV) is trajectory planning. However, the environmental differences faced by the near-space solar-powered UAV during lon...

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Bibliographic Details
Main Authors: Tichao Xu, Di Wu, Wenyue Meng, Wenjun Ni, Zijian Zhang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Flight strategy
guidance and control
near-space solar-powered aircraft
hierarchical reinforcement learning
energy management
trajectory planning
Online Access:https://ieeexplore.ieee.org/document/10416923/

Internet

https://ieeexplore.ieee.org/document/10416923/

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