Reinforcement Learning for Autonomous Underwater Vehicles via Data-Informed Domain Randomization

Autonomous Underwater Vehicles (AUVs) or underwater vehicle-manipulator systems often have large model uncertainties from degenerated or damaged thrusters, varying payloads, disturbances from currents, etc. Other constraints, such as input dead zones and saturations, make the feedback controllers di...

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Bibliographic Details

Published in:	Applied Sciences
Main Authors:	Wenjie Lu, Kai Cheng, Manman Hu
Format:	Article
Language:	English
Published:	MDPI AG 2023-01-01
Subjects:	autonomous underwater vehicles uncertainty attenuation reinforcement learning domain randomization
Online Access:	https://www.mdpi.com/2076-3417/13/3/1723