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On-board velocity estimation and closed-loop control of a quadrotor UAV based on optical flow

机译:基于光流的四旋翼无人机车载速度估计与闭环控制

摘要

Robot vision became a field of increasing importance in micro aerial vehicle robotics with the availability of small and light hardware. While most approaches rely on external ground stations because of the need of high computational power, we will present a full autonomous setup using only on-board hardware. Our work is based on the continuous homography constraint to recover ego-motion from optical flow. Thus we are able to provide an efficient fall back routine for any kind of UAV (Unmanned Aerial Vehicles) since we rely solely on a monocular camera and on on-board computation. In particular, we devised two variants of the classical continuous 4-point algorithm and provided an extensive experimental evaluation against a known ground truth. The results show that our approach is able to recover the ego-motion of a flying UAV in realistic conditions and by only relying on the limited on-board computational power. Furthermore, we exploited the velocity estimation for closing the loop and controlling the motion of the UAV online.
机译:随着小型轻巧的硬件的出现,机器人视觉已成为微型航空机器人中越来越重要的领域。虽然大多数方法由于需要高计算能力而依赖于外部地面站,但我们将仅使用板载硬件来提供完全自主的设置。我们的工作基于连续单应性约束,以从光流中恢复自我运动。因此,由于我们仅依赖于单眼相机和机载计算,因此我们能够为任何类型的无人机提供有效的后备程序。特别是,我们设计了经典连续4点算法的两个变体,并针对已知的地面事实提供了广泛的实验评估。结果表明,我们的方法仅依靠有限的机载计算能力就能够在现实条件下恢复飞行无人机的自我运动。此外,我们利用速度估计来闭合环路并在线控制无人机的运动。

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