71 citations · 368 across the 49 of their papers we have counts for
5 papers · 1 filter
Probabilistic Prediction of Ship Maneuvering Motion using Ensemble Learning with Feedforward Neural Networks
Kouki Wakita, Youhei Akimoto, Atsuo Maki
In the field of Maritime Autonomous Surface Ships (MASS), the accurate modeling of ship maneuvering motion for harbor maneuvers is a crucial technology. Non-parametric system ident…
Data Augmentation Methods of Dynamic Model Identification for Harbor Maneuvers using Feedforward Neural Network
Kouki Wakita, Yoshiki Miyauchi, Youhei Akimoto +1
A dynamic model for an automatic berthing and unberthing controller has to estimate harbor maneuvers, which include berthing, unberthing, approach maneuvers to berths, and entering…
Collision probability reduction method for tracking control in automatic docking / berthing using reinforcement learning
Kouki Wakita, Youhei Akimoto, Dimas M. Rachman +3
Automation of berthing maneuvers in shipping is a pressing issue as the berthing maneuver is one of the most stressful tasks seafarers undertake. Berthing control problems are ofte…
System Parameter Exploration of Ship Maneuvering Model for Automatic Docking / Berthing using CMA-ES
Yoshiki Miyauchi, Atsuo Maki, Naoya Umeda +2
Accurate maneuvering estimation is essential to establish autonomous berthing control. The system-based mathematical model is widely used to estimate the ship's maneuver. Commonly,…
On Neural Network Identification for Low-Speed Ship Maneuvering Model
Kouki Wakita, Atsuo Maki, Umeda Naoya +4
Several studies on ship maneuvering models have been conducted using captive model tests or computational fluid dynamics (CFD) and physical models, such as the maneuvering modeling…