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Simple UAV Environment (SUAVE): A viewpoint motion control evaluation

机译:简单无人机环境(SUAVE):视点运动控制评估

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Controlling a team of Unmanned Aerial Vehicles (UAV) requires the operator to perform continuous surveillance and path planning. The operator's situation awareness is likely to degrade as an increasing number of surveillance videos must be viewed and integrated. The Picture-in-Picture display (PiP) provides one solution for integrating multiple UAV camera video by allowing the operator to view the video feed in the context of surrounding terrain. The experimental SUAVE (Simple Unmanned Aerial Vehicle Environment) display extends PiP methods by sampling imagery from the video stream to texture a 3D map of the terrain. The operator can then inspect this imagery using world in miniature (WIM) or fly-through methods. Our previous investigation of the properties and advantages of SUAVE in the context of a search mission with 11 UAVs showed a strong advantage for finding targets. We investigated the effects of constrained versus unconstrained fly through technique to evaluate the performance in such spatially immersive displays. Results indicated no difference between these two motion control techniques.
机译:控制一支无人飞行器(UAV)团队需要操作员执行连续的监视和路径规划。随着必须观看和集成越来越多的监视视频,操作员的情况意识可能会下降。画中画显示器(PiP)通过允许操作员在周围地形的背景下查看视频源,提供了一种集成多个UAV摄像机视频的解决方案。实验性SUAVE(简单无人飞行器环境)显示通过从视频流中采样图像来扩展PiP方法,以绘制地形的3D地图。然后,操作员可以使用缩影世界(WIM)或飞越方法检查此图像。我们之前对SUAVE的特性和优势进行的调查表明,在使用11架无人机进行搜索任务的过程中,SUAVE具有寻找目标的强大优势。我们通过技术来研究约束飞行与非约束飞行的效果,以评估此类空间身临其境的显示器的性能。结果表明这两种运动控制技术之间没有差异。

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