仅用低成本摄像头实现无GPS环境下无人机自主导航与避障
GPS Denied IBVS-Based Navigation and Collision Avoidance of UAV Using a Low-Cost RGB Camera
- 基于图像的视觉伺服控制，无需路径规划
- 通过单目深度估计实现障碍物规避，实测有效
- 全系统部署在Jetson平台，适合实际飞行场景
本文提出一种仅使用RGB相机的基于图像的视觉伺服（IBVS）框架，用于无人机在无GPS环境下的导航与避障。尽管无人机导航已广泛研究，但在多视觉目标任务和避障场景中应用IBVS仍具挑战。所提方法实现无需显式路径规划的导航，碰撞规避通过从RGB图像进行人工智能驱动的单目深度估计实现。与依赖双目相机或外部工作站的方法不同，本框架可在Jetson平台上完全本地运行，构成自包含且可部署的系统。实验结果表明，无人机能在多个AprilTags间导航，并在无GPS环境下有效避开障碍物。
原文摘要 · Abstract (English)
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.
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