Reinforcement learning based recovery flight control for flapping-wing micro-aerial vehicles under extreme attitudes
This article deals with the recovery flight problem of flapping-wing micro-aerial vehicles under extreme attitude by using a reinforcement learning approach. First, the reinforcement learning-based control policy is proposed to enable the flapping-wing micro-aerial vehicles to be recovery flight rap...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-01-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/17298806241303290 |
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| Summary: | This article deals with the recovery flight problem of flapping-wing micro-aerial vehicles under extreme attitude by using a reinforcement learning approach. First, the reinforcement learning-based control policy is proposed to enable the flapping-wing micro-aerial vehicles to be recovery flight rapidly and keep the angular acceleration as small as possible. Then, a hybrid control approach is designed to significantly improve the flight stability by combining the reinforcement learning-based control approach with the proportional-derivative control approach. Finally, simulation results show the effectiveness of the reinforcement learning-based method and the hybrid control method for the flapping-wing micro-aerial vehicles under extreme attitudes. |
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| ISSN: | 1729-8814 |