collaborators

5 papers

eess.SY2026

Development and Identification of a Linear Low-Speed Ship Maneuvering Model from Full-Scale Data

Agnes N. Mwange, Taichi Kambara, Kouki Wakita +2

Despite significant technological progress, the realization of fully autonomous berthing and unberthing remains a significant challenge. One of the primary obstacles is the complex…

eess.SY2024

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…

eess.SY2024

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…

eess.SY2024

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…

eess.SY2024

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…