基于低成本的RGB相机在GPS拒止环境下利用IBVS的无人机导航与避障
GPS Denied IBVS-Based Navigation and Collision Avoidance of UAV Using a Low-Cost RGB Camera
AI总结：
本文提出一种仅依赖RGB相机和机载Jetson平台的IBVS框架，通过AI单目深度估计实现无路径规划的无人机导航与避障，并在GPS拒止环境下验证其有效性。
摘要：
本文提出了一种仅使用RGB相机的基于图像的视觉伺服（IBVS）框架，用于无人机导航与避障。尽管无人机导航已被广泛研究，但在涉及多个视觉目标和避障的任务中应用IBVS仍然具有挑战性。所提方法无需显式路径规划即可实现导航，避障则通过基于AI的RGB图像单目深度估计来实现。与依赖立体相机或外部工作站的方案不同，我们的框架完全在Jetson平台上机载运行，确保系统自成一体且可部署。实验结果验证了无人机能够在GPS拒止环境中穿越多个AprilTag并有效避开障碍物。
英文摘要：
This paper proposes an image-based visual servoing (IBVS) framework for UAV navigation and collision avoidance using only an RGB camera. While UAV navigation has been extensively studied, it remains challenging to apply IBVS in missions involving multiple visual targets and collision avoidance. The proposed method achieves navigation without explicit path planning, and collision avoidance is realized through AI-based monocular depth estimation from RGB images. Unlike approaches that rely on stereo cameras or external workstations, our framework runs fully onboard a Jetson platform, ensuring a self-contained and deployable system. Experimental results validate that the UAV can navigate across multiple AprilTags and avoid obstacles effectively in GPS-denied environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
