Dynamic Obstacle Avoidance for USVs Using Cross-Domain Deep Reinforcement Learning and Neural Network Model Predictive Controller

This work presents a framework that allows Unmanned Surface Vehicles (USVs) to avoid dynamic obstacles through initial training on an Unmanned Ground Vehicle (UGV) and cross-domain retraining on a USV. This is achieved by integrating a Deep Reinforcement Learning (DRL) agent that generates high-leve...

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Detalles Bibliográficos
Autores principales: Li, Jianwen, Chavez-Galaviz, Jalil, Azizzadenesheli, Kamyar, Mahmoudian, Nina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099039/
https://www.ncbi.nlm.nih.gov/pubmed/37050633
http://dx.doi.org/10.3390/s23073572

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099039/
https://www.ncbi.nlm.nih.gov/pubmed/37050633
http://dx.doi.org/10.3390/s23073572

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