Unmanned Aerial Vehicle Pitch Control Using Deep Reinforcement Learning with Discrete Actions in Wind Tunnel Test
Deep reinforcement learning is a promising method for training a nonlinear attitude controller for fixed-wing unmanned aerial vehicles. Until now, proof-of-concept studies have demonstrated successful attitude control in simulation. However, detailed experimental investigations have not yet been con...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-01-01
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| Series: | Aerospace |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2226-4310/8/1/18 |