论文标题
Newton-PNP：自动玩具无人机的实时视觉导航
Newton-PnP: Real-time Visual Navigation for Autonomous Toy-Drones
论文作者
论文摘要
Perspective-N点问题旨在通过将2D捕获的图像点对齐对与模型中相应的3D点的对齐对进行对齐对，以估算校准的单眼相机和已知3D模型之间的相对姿势。我们建议一种实时在弱的物联网设备上运行的算法，但仍然可以为运行时间和正确性提供可证明的理论保证。现有求解器仅提供这些要求之一。我们的主要动机是将受欢迎的DJI的Tello无人机（<90gr，<\ $ 100）转变为自动无人机，该无人机只需将Raspberry Pi Zero（<9gr，<\ $ 25）附加到室内环境中，而没有外部人/笔记本电脑/传感器。这个微小的微型处理器将其作为从微型RGB摄像头输入实时视频，并在板载板上运行我们的PNP求解器。包括广泛的实验结果，开源代码和演示视频。
The Perspective-n-Point problem aims to estimate the relative pose between a calibrated monocular camera and a known 3D model, by aligning pairs of 2D captured image points to their corresponding 3D points in the model. We suggest an algorithm that runs on weak IoT devices in real-time but still provides provable theoretical guarantees for both running time and correctness. Existing solvers provide only one of these requirements. Our main motivation was to turn the popular DJI's Tello Drone (<90gr, <\$100) into an autonomous drone that navigates in an indoor environment with no external human/laptop/sensor, by simply attaching a Raspberry PI Zero (<9gr, <\$25) to it. This tiny micro-processor takes as input a real-time video from a tiny RGB camera, and runs our PnP solver on-board. Extensive experimental results, open source code, and a demonstration video are included.
