论文标题
小型无人飞机系统的虚拟测试床
Virtual Testbed for Monocular Visual Navigation of Small Unmanned Aircraft Systems
论文作者
论文摘要
在过去的十年中，单眼视觉导航方法取得了重大进展，最近生产了几种实时解决方案，用于自主在而无需依赖GP的小型无人飞机系统。这对于可能涉及GPS信号降级或拒绝的环境的军事行动至关重要。但是，由于视觉数据的收集价格昂贵，因此测试和比较视觉导航算法仍然是一个挑战。在承诺户外测试之前，在虚拟环境中进行飞行测试是一个有吸引力的解决方案。 这项工作提出了一个虚拟测试床，用于对现实世界地形进行模拟飞行测试，并分析31 Hz的视觉导航算法的实时性能。该工具的创建是为了最终找到适合于固定翼飞机进一步受到GPS有限的导航研究的视觉探针算法，即使所有算法都是为其他模式设计的。该测试台用于评估固定翼平台上的三个当前最新的，开源的单眼视觉探视算法：直接稀疏探针仪，半独立视觉探视和ORB-SLAM2（禁用了LOOP闭合）。
Monocular visual navigation methods have seen significant advances in the last decade, recently producing several real-time solutions for autonomously navigating small unmanned aircraft systems without relying on GPS. This is critical for military operations which may involve environments where GPS signals are degraded or denied. However, testing and comparing visual navigation algorithms remains a challenge since visual data is expensive to gather. Conducting flight tests in a virtual environment is an attractive solution prior to committing to outdoor testing. This work presents a virtual testbed for conducting simulated flight tests over real-world terrain and analyzing the real-time performance of visual navigation algorithms at 31 Hz. This tool was created to ultimately find a visual odometry algorithm appropriate for further GPS-denied navigation research on fixed-wing aircraft, even though all of the algorithms were designed for other modalities. This testbed was used to evaluate three current state-of-the-art, open-source monocular visual odometry algorithms on a fixed-wing platform: Direct Sparse Odometry, Semi-Direct Visual Odometry, and ORB-SLAM2 (with loop closures disabled).
