Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

Executing accurate trajectory tracking tasks using a high-performance low-level controller is crucial for quadrotors to be applied in various scenarios, especially those involving uncertain disturbances. However, due to the uncertainties in disturbed environments, developing effective low-level cont...

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Veröffentlicht in:	Neural computing & applications Jg. 37; H. 3; S. 1223 - 1240
Hauptverfasser:	Chen, Shiyu, Li, Yanjie, Lou, Yunjiang, Lin, Ke
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.01.2025 Springer Nature B.V
Schlagworte:	Accuracy Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Control algorithms Control methods Controllers Data Mining and Knowledge Discovery Deep learning Disturbances Hovering Image Processing and Computer Vision Initial conditions Methods Original Article Probability and Statistics in Computer Science Proportional integral derivative Robotics Robust control Rotary wing aircraft Simulation Tracking Unmanned aerial vehicles Velocity Vibration control Robustness Trajectory tracking Low-level control Reinforcement learning Quadrotor
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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