基于视觉的水下无人艇实时定位导航与建图框架
A Vision-based Control Framework for Real-time Autonomous UUV Operations
- 融合视觉信息实现水下实时定位与连续3D建图
- 支持相对网位与全局定位，动态环境鲁棒性强
- 适合复杂水下场景的巡检与测绘任务
本文提出一种完全集成的基于视觉的框架，用于在动态、视觉挑战性环境中实现水下无人航行器（UUV）的实时、鲁棒定位、自主导航与地图构建。该方案支持相对于网位和全局的定位，并实现实时连续3D环境建图。框架在带真实标注的合成数据集上验证，并在实际水下无人艇上完成了自主网位导航实验。结果表明，系统具备实时性能与增强的鲁棒性，支持视觉驱动的自主导航，可应用于复杂水下环境中关键巡检与测绘任务的现场部署。
原文摘要 · Abstract (English)
This paper presents a fully integrated vision-based framework for real-time and robust localization, autonomous navigation, and mapping for unmanned underwater vehicles (UUVs) in dynamic, visually challenging environments. The proposed pipeline enables both net-relative and global localization while generating continuous 3D maps of the surroundings in real-time. The framework was validated on synthetic datasets with ground truth and tested onboard an UUV during autonomous net-relative navigation experiments. Results demonstrate real-time performance and enhanced robustness, supporting vision-driven autonomous navigation and enabling the field deployment of marine robots for critical inspection and mapping tasks in complex underwater environments.
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