Automatic berthing using supervised learning and reinforcement learning
Shoma Shimizu(Yokohama National University), Shinichi Shirakawa(Yokohama National University), Rin Suyama(The University of Osaka), Atsuo Maki(Museum of Japanese Art Yamato Bunkakan), Kouki Wakita(University of Tsukuba), Yoshiki Miyauchi(The University of Osaka), Kenta Nishihara(Yokohama National University)
Cited by 42
Related Papers
On neural network identification for low-speed ship maneuvering model
|Journal of Marine Science and Technology|2022|68
Parameter fine-tuning method for MMG model using real-scale ship data
|Ocean Engineering|2024|15
Collision probability reduction method for tracking control in automatic docking/berthing using reinforcement learning
|Journal of Marine Science and Technology|2023|14
Data augmentation methods of dynamic model identification for harbor maneuvers using feedforward neural network
|Journal of Marine Science and Technology|2024|9
On Neural Network Identification for Low-Speed Ship Maneuvering Model
|arXiv (Cornell University)|2021|6