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

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

Internet

https://www.mdpi.com/2076-3417/13/3/1723

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