Energy Optimal Trajectory Planning for the Morphing Solar-Powered Unmanned Aerial Vehicle Based on Hierarchical Reinforcement Learning
Trajectory planning is crucial for solar aircraft endurance. The multi-wing morphing solar aircraft can enhance solar energy acquisition through wing deflection, which simultaneously incurs aerodynamic losses, complicating energy coupling and challenging existing planning methods in efficiency and l...
Saved in:
| Main Authors: | Tichao Xu, Wenyue Meng, Jian Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/7/498 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Status and Development Prospects of Solar-Powered Unmanned Aerial Vehicles—A Literature Review
by: Krzysztof Sornek, et al.
Published: (2025-04-01) -
Hierarchical Reinforcement Learning with Automatic Curriculum Generation for Unmanned Combat Aerial Vehicle Tactical Decision-Making in Autonomous Air Combat
by: Yang Li, et al.
Published: (2025-05-01) -
A Hierarchical Deep Reinforcement Learning Approach for Throughput Maximization in Reconfigurable Intelligent Surface-Aided Unmanned Aerial Vehicle–Integrated Sensing and Communication Network
by: Haitao Chen, et al.
Published: (2024-11-01) -
Deep Reinforcement Learning-Driven Jamming-Enhanced Secure Unmanned Aerial Vehicle Communications
by: Zhifang Xing, et al.
Published: (2024-11-01) -
Enhancing Unmanned Aerial Vehicle Path Planning in Multi-Agent Reinforcement Learning through Adaptive Dimensionality Reduction
by: Haotian Shi, et al.
Published: (2024-09-01)