Model‐Free Deep Reinforcement Learning with Multiple Line‐of‐Sight Guidance Laws for Autonomous Underwater Vehicles Full‐Attitude and Velocity Control

Autonomous underwater vehicles (AUVs) are increasingly utilized, driving the need for enhanced autonomy. Conventional proportional–integral–derivative (PID) algorithms require frequent control parameter adjustments under varying voyage conditions, which increases operational and experimental costs....

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Bibliographic Details
Main Authors: Chengren Yuan, Changgeng Shuai, Zhanshuo Zhang, Jianguo Ma, Yuan Fang, YuChen Sun
Format: Article
Language:English
Published: Wiley 2025-08-01
Series:Advanced Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1002/aisy.202400991
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