Learning Adaptive Control of a UUV Using a Bio-Inspired Experience Replay Mechanism

Deep Reinforcement Learning (DRL) methods are increasingly being applied in Unmanned Underwater Vehicles (UUV) providing adaptive control responses to environmental disturbances. However, in physical platforms, these methods are hindered by their inherent data inefficiency and performance degradatio...

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主要な著者:	Thomas Chaffre, Paulo E. Santos, Gilles Le Chenadec, Estelle Chauveau, Karl Sammut, Benoit Clement
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2023-01-01
シリーズ:	IEEE Access
主題:	Deep reinforcement learning machine learning adaptive control underwater robotics
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10304148/
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