Seeing above the waves: A modular sensing framework for data acquisition at sea

2026-08-11

AI Summary

This work addresses the lack of reproducible and modular sensor platforms for maritime autonomous vehicles, which hinders systematic evaluation of perception systems. To this end, we present the first standardized, extensible multimodal sensing platform tailored for maritime autonomy, integrating RADAR, LiDAR, IMU, GNSS, AIS, RGB/LWIR cameras, and meteorological sensors. Built upon ROS 2, the platform features a unified hardware architecture and data acquisition framework that supports long-term deployment, multi-vessel coordination, hardware-in-the-loop testing, and seamless algorithm integration. By ensuring consistent data collection and system interoperability, our solution significantly enhances the reproducibility, cross-platform comparability, and reliability of maritime perception systems, thereby establishing a robust foundation for situational awareness and autonomous navigation at sea.

Abstract

Advancing autonomy for surface vessels requires systematic evaluation of their sensing and perception subsystems. Yet, maritime environments impose unique challenges: sensor installation is constrained by vessel layout, environmental conditions such as fog or sea clutter are difficult to reproduce, and long-duration missions complicate data collection. This work addresses the question: How can we design a modular and reproducible sensor platform for maritime autonomy? We present a comprehensive design blueprint that incorporates diverse modalities - RADAR, LiDAR, IMU, GNSS, AIS, RGB and LWIR cameras, and weather sensors - to enhance environmental awareness and vessel proprioception. Supported by a dedicated ROS2-based software framework for data management, our modular platform enables long-term data collection, hardware-in-the-loop testing, and integration with existing sensors and algorithms. By unifying hardware design and data capture methodology, the platform enhances reproducibility and comparability across vessels and research projects. The proposed framework bridges engineering implementation and research methodology, providing the foundation for standardized, verifiable datasets essential to advancing situational awareness and autonomous maritime navigation.

Problem

• modular sensing
• maritime autonomy
• sensor platform
• data acquisition
• reproducibility

Innovation

• modular sensing
• maritime autonomy
• multi-modal sensor fusion
• ROS2 framework
• reproducible data collection