用单目相机和光流实现微型无人机无先验自主导航
MinNav: Minimalist Navigation Using Optical Flow For Active Tiny Aerial Robots
- 基于光流与不确定性构建轻量导航系统
- 70%成功率通过真实场景验证，含动态障碍与未知缝隙
- 计算量仅为深度方法的数分之一，适合微型飞行器部署
单目相机导航对微型空中机器人的自主运行至关重要，因其在灵活性、成本与精度之间取得理想平衡。本文提出MinNav导航系统，利用光流及其不确定性，在无需预先了解场景结构或障碍物位置顺序的情况下，实现对静态与动态障碍物及未知形状间隙的穿越。通过主动探索式运动提升成功概率。在多种真实环境中的实验表明，整体成功率达70%。据我们所知，这是首个仅依赖单目相机且无需先验知识即可应对上述所有复杂场景的解决方案。该方法性能媲美基于深度的方法，但计算量仅为后者的数分之一，可直接部署于微型空中机器人上。配套视频、补充材料、代码与数据集见https://pear.wpi.edu/research/minnav.html。
原文摘要 · Abstract (English)
Navigation using a monocular camera is pivotal for autonomous operation on tiny aerial robots due to their perfect balance of versatility, cost and accuracy. In this paper, we introduce MinNav, a navigation stack based on optical flow and its uncertainty to fly through a scene with static and dynamic obstacles and unknown-shaped gaps without any prior knowledge of the scene components and/or their locations/ordering. We further improve success rate by using the activeness of the robot to move around in an exploratory way to find obstacles and navigate. We successfully evaluate and demonstrate the proposed approach in many real-world experiments in various environments with static and dynamic obstacles and unknown-shaped gaps with an overall success rate of 70%. To the best of our knowledge, this is the first solution to tackle all the aforementioned navigation cases without prior knowledge using a monocular camera. Our approach is on par in performance with depth based methods with factors of magnitude less computation required and can readily run onboard tiny aerial robots. The accompanying video, supplementary material, code and dataset can be found at https://pear.wpi.edu/research/minnav.html
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