This paper demonstrates an approach to the vision-based control of the unmanned quadrotors for hover and object tracking. The algorithms used the Speed Up Robust Features (SURF) algorithm to detect objects. The pose of the object in the image was then calculated in order to pass the pose information to the flight controller. Finally, the flight controller steered the quadrotor to approach the object based on the calculated pose data. The above processes was run using standard onboard resources found in the 3DR Solo quadrotor in an embedded computing environment. The obtained results showed that the algorithm behaved well during its missions, tracking and hovering, although there were significant latencies due to low CPU performance of the onboard image processing system.
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机译：本文展示了一种用于悬停和对象跟踪的无人压谐波的视觉控制的方法。该算法使用速度升高的鲁棒特征（冲浪）算法来检测对象。然后计算图像中的对象的姿势，以便将姿势信息传递给飞行控制器。最后，飞行控制器引导了四轮压力机以基于计算出的姿势数据来接近对象。在嵌入式计算环境中使用3dr Solo Quadrotor中找到的标准板载资源运行上述进程。所获得的结果表明，该算法在其任务期间表现良好，跟踪和悬停，尽管由于车载图像处理系统的低CPU性能而导致具有显着的延迟。
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