面向低成本自主水下航行器的仅被动传感器高效视觉-惯性SLAM
Towards Effective Visual-Inertial SLAM with Passive-Only Sensors for Low-Cost Autonomous Underwater Vehicles
- University of Minnesota–Twin Cities（明尼苏达大学双城分校）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究证明，利用低于1万美元的消费级传感器平台，通过优化传感器融合的VI-SLAM，可实现低成本AUV在6-DOF水下环境中的稳健导航，为大众提供可用的SLAM基准。
AI中文摘要：
改进低成本自主水下航行器（AUVs）的视觉-惯性同时定位与建图（VI-SLAM）技术，对于将先进海洋机器人从专业实验室推广到更广泛的研究和爱好者应用至关重要。虽然高端AUV通常依赖昂贵的传感器套件——如多普勒测速仪（DVLs）和超短基线（USBL）系统——但本工作证明，使用仅配备廉价消费级传感器的低于10,000美元（USD）平台即可实现稳健、高质量的导航。通过利用一个价格相近的开源AUV，我们在完全无约束的6自由度（6-DOF）水下环境中评估了立体相机、基于微机电系统（MEMS）的惯性测量单元（IMUs）和深度传感器的性能。我们分析了现成SLAM包的有效性，并提出了传感器融合的优化方案，以缓解无缆水下作业的视觉和物理挑战。我们的结果证明，可用的SLAM解决方案可以普及到大众，为要求严苛的实时海上任务提供了期望基准，而无需承受工业级硬件的经济负担。
英文摘要：
Improvements to Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) for low-cost autonomous underwater vehicles (AUVs) are critical for transitioning advanced marine robotics from specialized labs to broader research and hobbyist applications. While high-end AUVs typically rely on expensive sensor suites - such as Doppler Velocity Logs (DVLs) and Ultra-Short Baseline (USBL) systems - this work demonstrates that robust, high-quality navigation is achievable using a sub-$10, 000(USD) platform equipped only with inexpensive consumer-grade sensors. By leveraging a similarly priced, open-source AUV, we evaluate the performance of stereo cameras, Micro-electromechanical System (MEMS)-based IMUs, and depth sensors in a fully unconstrained 6-degree-of-freedom (6-DOF) underwater environment. We analyze the efficacy of off-the-shelf SLAM packages and propose optimizations for sensor fusion to mitigate the visual and physical challenges of untethered underwater operation. Our results prove that a usable SLAM solution can be accessible to the masses, providing a benchmark for expectations in demanding, real-time maritime missions without the financial barrier of industrial-grade hardware.
