Design and Experimental Validation of an Autonomous USV for Sensor Fusion-Based Navigation in GNSS-Denied Environments

• URL: http://arxiv.org/abs/2503.23445v1
• Date: Sun, 30 Mar 2025 13:50:46 GMT
• Title: Design and Experimental Validation of an Autonomous USV for Sensor Fusion-Based Navigation in GNSS-Denied Environments
• Authors: Samuel Cohen-Salmon, Itzik Klein,
• Abstract summary: MARVEL is an unmanned surface vehicle built for real-world testing of sensor fusion-based navigation algorithms in-denied environments.<n>It integrates electromagnetic logs, Doppler velocity logs, inertial sensors, and real-time kinematic positioning.<n>MARVEL enables real-time, in-situ validation of advanced navigation and AI-driven algorithms using redundant, synchronized sensors.
• Score: 2.915868985330569
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents the design, development, and experimental validation of MARVEL, an autonomous unmanned surface vehicle built for real-world testing of sensor fusion-based navigation algorithms in GNSS-denied environments. MARVEL was developed under strict constraints of cost-efficiency, portability, and seaworthiness, with the goal of creating a modular, accessible platform for high-frequency data acquisition and experimental learning. It integrates electromagnetic logs, Doppler velocity logs, inertial sensors, and real-time kinematic GNSS positioning. MARVEL enables real-time, in-situ validation of advanced navigation and AI-driven algorithms using redundant, synchronized sensors. Field experiments demonstrate the system's stability, maneuverability, and adaptability in challenging sea conditions. The platform offers a novel, scalable approach for researchers seeking affordable, open-ended tools to evaluate sensor fusion techniques under real-world maritime constraints.

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