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Autonomous landing of an UAV with a ground-based actuated infrared stereo vision system

机译:带有地面启动式红外立体视觉系统的无人机自动降落

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In this study, we focus on the problem of landing an unmanned aerial vehicle (UAV) in unknown and Global Navigation Satellite System(GNSS)-denied environments based on an infrared stereo vision system. This system is fixed on the ground and used to track the UAV's position during the landing process. In order to enlarge the search field of view (FOV), a pan-tilt unit (PTU) is employed to actuate the vision system. The infrared camera is chosen as the exteroceptive sensor for two main reasons: first, it can be used under all weather conditions and around the clock; second, infrared targets can be tracked based on infrared spectrum features at a lower computational cost compared to tracking texture features in visible spectrum. State-of-the-art active contour based algorithms and the mean shift algorithm have been evaluated with regard to detecting and tracking an infrared target. Field experiments have been carried out using an unmanned quadrotor and a fixed-wing unmanned aircraft, with both qualitative and quantitative evaluations. The results demonstrate that our system can track UAVs without artificial markers and is sufficient to enhance or replace the GNSS-based localization in GNSS-denied environment or where its information is inaccurate.
机译:在这项研究中,我们着重于在基于红外立体视觉系统的未知和全球导航卫星系统(GNSS)受限的环境中着陆无人飞行器(UAV)的问题。该系统固定在地面上,用于在着陆过程中跟踪无人机的位置。为了扩大搜索视野(FOV),采用了云台装置(PTU)来启动视觉系统。选择红外热像仪作为外感传感器有两个主要原因:首先,它可以在所有天气条件下全天候使用;其次,与跟踪可见光谱中的纹理特征相比,可以基于红外光谱特征以较低的计算成本来跟踪红外目标。在检测和跟踪红外目标方面,已经评估了基于主动轮廓的最新算法和均值偏移算法。已经使用无人四旋翼飞机和固定翼无人飞机进行了现场实验,并进行了定性和定量评估。结果表明,我们的系统无需使用人工标记即可跟踪无人机,并且足以增强或替代GNSS受限环境或信息不准确的基于GNSS的定位。

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