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Spectral ladar as a UGV navigation sensor

机译:光谱雷达作为UGV导航传感器

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We demonstrate new results using our Spectral LADAR prototype, which highlight the benefits of this sensor for Unmanned Ground Vehicle (UGV) navigation applications. This sensor is an augmentation of conventional LADAR and uses a polychromatic source to obtain range-resolved 3D spectral point clouds. These point cloud images can be used to identify objects based on combined spatial and spectral features in three dimensions and at long standoff range. The Spectral LADAR transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Backscatter from distant targets is dispersed into 25 spectral bands, where each spectral band is independently range resolved with multiple return pulse recognition. Our new results show that Spectral LADAR can spectrally differentiate hazardous terrain (mud) from favorable driving surfaces (dry ground). This is a critical capability, since in UGV contexts mud is potentially hazardous, requires modified vehicle dynamics, and is difficult to identify based on 3D spatial signatures. Additionally, we demonstrate the benefits of range resolved spectral imaging, where highly cluttered 3D images of scenes (e.g. containing camouflage, foliage) are spectrally unmixed by range separation and segmented accordingly. Spectral LADAR can achieve this unambiguously and without the need for stereo correspondence, sub-pixel detection algorithms, or multi-sensor registration and data fusion.
机译:我们使用我们的光谱LADAR原型演示了新结果,该原型突出了该传感器在无人地面车辆(UGV)导航应用中的优势。该传感器是常规LADAR的增强,并使用多色光源获得距离分辨的3D光谱点云。这些点云图像可用于基于三维空间和远距离范围内的组合空间和光谱特征来识别对象。光谱LADAR传输在光子晶体光纤中产生的纳秒级超连续谱脉冲。来自远距离目标的反向散射被分散到25个光谱带中,其中每个光谱带通过多个返回脉冲识别独立地进行范围分辨。我们的新结果表明,光谱LADAR可以从有利的行驶表面(干燥地面)光谱区分危险地形(泥浆)。这是一项关键功能,因为在UGV环境中,泥浆可能具有潜在危险,需要修改车辆动力学,并且很难基于3D空间特征进行识别。此外,我们展示了距离分辨光谱成像的优势,其中场景高度杂乱的3D图像(例如,包含迷彩,树叶)通过距离分离在光谱上未混合并相应地进行了分割。光谱LADAR可以毫无疑问地实现这一点,而无需立体对应,子像素检测算法或多传感器配准和数据融合。

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