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Reinforcement Learning-Based Tracking Control of USVs in Varying Operational Conditions

We present a reinforcement learning-based (RL) control scheme for trajectory tracking of fully-actuated surface vessels. The proposed method learns online both a model-based feedforward controller, as well an optimizing feedback policy in order to follow a desired trajectory under the influence of e...

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Bibliografische gegevens
Gepubliceerd in:Front Robot AI
Hoofdauteurs: Martinsen, Andreas B., Lekkas, Anastasios M., Gros, Sébastien, Glomsrud, Jon Arne, Pedersen, Tom Arne
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Frontiers Media S.A. 2020
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7806118/
https://ncbi.nlm.nih.gov/pubmed/33501200
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frobt.2020.00032
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