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LAPS-II: 6-DoF day and night visual localisation with prior 3D structure for autonomous road vehicles

机译:LAPS-II:6-DoF白天和夜晚的视觉定位,以及用于自动公路车辆的先前3D结构

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Robust and reliable visual localisation at any time of day is an essential component towards low-cost autonomy for road vehicles. We present a method to perform online 6-DoF visual localisation across a wide range of outdoor illumination conditions throughout the day and night using a 3D scene prior collected by a survey vehicle. We propose the use of a one-dimensional illumination invariant colour space which stems from modelling the spectral properties of the camera and scene illumination in conjunction. We combine our previous work on Localisation with Appearance of Prior Structure (LAPS) with this illumination invariant colour space to demonstrate a marked improvement in our ability to localise throughout the day compared to using a conventional RGB colour space. Our ultimate goal is robust and reliable any-time localisation — an attractive proposition for low-cost autonomy for road vehicles. Accordingly, we demonstrate our technique using 32km of data collected over a full 24-hour period from a road vehicle.
机译:在一天中的任何时候,稳健而可靠的视觉定位都是实现道路车辆低成本自动驾驶的重要组成部分。我们提出了一种方法,可以使用调查车辆事先收集的3D场景,在白天和黑夜中,在广泛的室外照明条件下执行在线6自由度视觉本地化。我们建议使用一维照明不变的色彩空间,该色彩空间源于对相机的光谱特性和场景照明进行联合建模。我们将以前的定位与先验结构的外观(LAPS)结合在一起,并结合了照明不变的色彩空间,以证明与使用常规RGB色彩空间相比,我们全天的定位能力得到了显着提高。我们的最终目标是随时随地进行可靠可靠的本地化,这是公路车辆低成本自主发展的诱人主张。因此,我们使用从公路车辆整整24小时内收集到的32公里数据演示了我们的技术。

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