Open source simulator for maritime robotics researchers
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Updated
Jan 16, 2024 - Python
Open source simulator for maritime robotics researchers
A python framework to predict trajectories of vessels with machine learning algorithms, such as lstm, seq2seq, etc.
WaSR Segmentation Network for Unmanned Surface Vehicles v0.5
[NeurIPS 2025 Spotlight] Neptune-X: Active X-to-Maritime Generation for Universal Maritime Object Detection
A PyTorch reimplementation of the WaSR obstacle segmentation model
Detecting automatic identification system (AIS) on-off switching anomalies, unusual turn detection, and deviation of trajectories of vessels.
Marine vessel tracking tool by geolocation, MMSI, or MarineTraffic URLs
Temporal WaSR-T model for maritime obstacle detection via semantic segmentation
Anomaly detection in maritime navigation with evidential deep learning based on graph-based clustering
Evaluation scripts for the LaRS dataset
A generator for synthetic container flows at maritime container terminals with a focus on yard operations
An Acoustic and Optical Dataset for the Perception of Underwater Unexploded Ordnance (UXO)
Maritime route optimization system for MR Product Tankers. Weather-aware A* routing, Holtrop-Mennen vessel modeling, Copernicus data integration, CII compliance, and live sensor fusion.
Scaffolded Learning Regime for training maritime obstacle detection networks
CLI tool for accessing maritime intelligence via Equasis database - comprehensive vessel data with management details, inspection history, and ownership tracking
Cartographic Sounding Selection for ENCs
The Equasis Data Fetcher is a Streamlit-based web application designed to retrieve and analyze maritime vessel information from the Equasis database. It offers functionalities for fetching detailed information about vessels and entire fleets, and it provides an interface for querying this data using natural language questions powered by OpenAI.
Simulation of transhipment logistics between 2 different locations to ascertain its timeliness in arrival. This project was inspired by a Simulation Project that i worked on as a Capacity Planner and Analyst at PSA Singapore.
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