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Fast horizon detection for airborne visual systems

机译:空机视觉系统的快速地平线检测

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In this paper a fast horizon detection algorithm is introduced, which is run on an airborne visual system. It is important to run the horizon detection as fast as possible, and also with low power consumption. Hence we developed an algorithm, which has low complexity. The horizon detection uses attitude information provided by the flight control computer of the aircraft and it corrects the horizon based on the visual information from our airborne camera system. All calculations are run onboard, and the detected horizon is used in the sense-and-avoid task for sky-ground separation. The performance of the algorithm is measured in flight tests, which shows that it has superior performance compared to the horizon calculated from the attitude provided by the autopilot and also compared to the horizon calculated from the Euler angles given by our Kalman filter based attitude estimator. The measurements were run on videos from two cameras next to other sensors' information, which were recorded in November 2015. The videos were annotated by hand, which were used as a ground truth.
机译:在本文中,引入了一种快速地平线检测算法,其在机载的视觉系统上运行。重要的是尽可能快地运行地平线检测,并且还具有低功耗。因此,我们开发了一种具有低复杂性的算法。地平线检测使用飞机的飞行控制计算机提供的姿态信息,并根据我们的空气传播的相机系统的视觉信息来校正地平线。所有计算都运行,检测到的地平线用于Sense-and-避免用于天空地分离的任务。算法的性能在飞行试验中测量,表明它具有与自动驾驶仪提供的姿势计算的地平线相比的优越性,并且与由我们的卡尔曼滤波器的姿态估计器给出的欧拉角计算的地平线相比。测量在其他传感器信息旁边的两个摄像机上运行,​​该信息于2015年11月录制。该视频用手注释,被用作地面真理。

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