Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments
Author:
Affiliation:
1. Department of Mathematics and Cybernetics, SINTEF DIGITAL, Oslo, Norway
2. Department of Engineering Cybernetics, Centre for Autonomous Marine Operations and Systems, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
Funder
Research Council of Norway through Ph
through the Centres of Excellence Funding Scheme
NTNU AMOS and
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software
Link
http://xplorestaging.ieee.org/ielx7/5962385/6104215/10101867.pdf?arnumber=10101867
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Data-Driven Aircraft Modeling for Robust Reinforcement Learning Control Synthesis With Flight Test Validation;Journal of Dynamic Systems, Measurement, and Control;2024-08-17
2. Deep reinforcement learning-based reactive trajectory planning method for UAVs;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2024-05-07
3. Interchangeable Reinforcement-Learning Flight Controller for Fixed-Wing UASs;IEEE Transactions on Aerospace and Electronic Systems;2024-04
4. A Review of Reinforcement Learning for Fixed-Wing Aircraft Control Tasks;IEEE Access;2024
5. A Transfer Reinforcement Learning-Based Control Method for Vertical n-Link Underactuated Manipulator With Two Passive Joints;IEEE/ASME Transactions on Mechatronics;2024
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