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Mitigating the effects of boom occlusion on automated aerial refueling through shadow volumes

机译:通过阴影区减轻动臂阻塞对自动空中加油的影响

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In-flight refueling of unmanned aerial vehicles (UAVs) is critical to the United States Air Force (USAF). However, the large communication latency between a ground-based operator and his/her remote UAV makes docking with a refueling tanker unsafe. This latency may be mitigated by leveraging a tanker-centric stereo vision system. The vision system observes and computes an approaching receiver’s relative position and orientation offering a low-latency, high frequency docking solution. Unfortunately, the boom – an articulated refueling arm responsible for physically pumping fuel into the receiver – occludes large portions of the receiver especially as the receiver approaches and docks with the tanker. The vision system must be able to compensate for the boom’s occlusion of the receiver aircraft. We present a novel algorithm for mitigating the negative effects of boom occlusion in stereo-based aerial environments. Our algorithm dynamically compensates for occluded receiver geometry by transforming the occluded areas into shadow volumes. These shadow volumes are then used to cull hidden geometry that is traditionally consumed, in error, by the vision processing and point registration pipeline. Our algorithm improves computer-vision pose estimates by 44% over a naïve approach without shadow volume culling.
机译:无人机的空中加油对美国空军(USAF)至关重要。但是,地面操作员与他/她的远程UAV之间的通信等待时间较长,因此与加油机对接不安全。通过利用以油轮为中心的立体视觉系统,可以减轻这种等待时间。视觉系统观察并计算接近的接收器的相对位置和方向,从而提供一种低延迟,高频对接解决方案。不幸的是,动臂(一个用于将燃料物理地泵入接收器的铰接加油臂)堵塞了接收器的大部分,特别是当接收器接近并与加油机对接时。视觉系统必须能够补偿接收器飞机的吊杆闭塞。我们提出了一种新颖的算法,用于减轻基于立体声的空中环境中的臂杆闭塞的负面影响。我们的算法通过将遮挡的区域转换为阴影体积来动态补偿遮挡的接收器几何形状。然后,将这些阴影体积用于消除视觉处理和点配准管线错误地消耗的传统隐藏几何。我们的算法在没有阴影体积剔除的情况下,较单纯的方法将计算机视觉姿态估计提高了44%。

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