# Pohang Canal Dataset: A Multimodal Maritime Dataset for Autonomous Navigation in Restricted Waters

arXiv: https://arxiv.org/abs/2303.05555 · HTML: https://mlsanity.com/paper/2303.05555/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Mar 2023.

## Built on by (most cited first, 5 of 5)

- [WaterVG: Waterway Visual Grounding based on Text-Guided Vision and mmWave Radar](https://mlsanity.com/paper/2403.12686/) (2024)
- [SeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles](https://mlsanity.com/paper/2404.18411/) (2024)
- [MOANA: Multi-Radar Dataset for Maritime Odometry and Autonomous Navigation Application](https://mlsanity.com/paper/2412.03887/) (2024)
- [Good Deep Features to Track: Self-Supervised Feature Extraction and Tracking in Visual Odometry](https://mlsanity.com/paper/2509.08333/) (2025)
- [WHU-PCPR: A cross-platform heterogeneous point cloud dataset for place recognition in complex urban scenes](https://mlsanity.com/paper/2601.06442/) (2026)

## Abstract (arXiv)

This paper presents a multimodal maritime dataset and the data collection procedure used to gather it, which aims to facilitate autonomous navigation in restricted water environments. The dataset comprises measurements obtained using various perception and navigation sensors, including a stereo camera, an infrared camera, an omnidirectional camera, three LiDARs, a marine radar, a global positioning system, and an attitude heading reference system. The data were collected along a 7.5-km-long route that includes a narrow canal, inner and outer ports, and near-coastal areas in Pohang, South Korea. The collection was conducted under diverse weather and visual conditions. The dataset and its detailed description are available for free download at https://sites.google.com/view/pohang-canal-dataset.