DRL-Based Thruster Fault Recovery for Unmanned Underwater Vehicles
Author:
Affiliation:
1. Lab-STICC UMR CNRS 6285, ENSTA Bretagne,Brest,France
2. Naval Group Research,Ollioules,France
3. Flinders University,Adelaide,Australia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10432770/10432788/10432828.pdf?arnumber=10432828
Reference25 articles.
1. Evaluation of a Deep-Reinforcement-Learning-based Controller for the Control of an Autonomous Underwater Vehicle
2. Direct Adaptive Pole-Placement Controller using Deep Reinforcement Learning: Application to AUV Control
3. Learning Adaptive Control of a UUV Using a Bio-Inspired Experience Replay Mechanism
4. UUV Simulator: A Gazebo-based package for underwater intervention and multi-robot simulation
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