低成本无人船实现海上无卫星导航环境下的实时融合定位验证。
Design and Experimental Validation of an Autonomous USV for Sensor Fusion-Based Navigation in GNSS-Denied Environments
- 构建模块化无人船，融合多传感器数据进行高精度定位。
- 实测证明系统在复杂海况下稳定、可操控且适应性强。
- 适合研究者用于低成本真实海洋场景的导航算法实验。
本文介绍了MARVEL无人水面艇的设计、开发与实验验证，该平台专为在无全球导航卫星系统（GNSS）环境下测试基于传感器融合的导航算法而设计。MARVEL在成本效益、便携性和海上适航性方面严格受限，旨在提供一个模块化、易获取的平台，用于高频数据采集与实验学习。其集成电磁计程仪、多普勒速度仪、惯性传感器及实时动态GNSS定位。该系统支持利用冗余同步传感器，对先进导航与人工智能驱动算法进行实时、现场验证。实地实验表明，系统在复杂海况下具备良好的稳定性、机动性与适应性。该平台为研究人员提供了一种新颖、可扩展的低成本、开放式工具，可用于评估真实海洋约束下的传感器融合技术。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。