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

William P. Maddern, Alexander D. Stewart, P. Newman
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引用次数: 35

Abstract

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.
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LAPS-II:用于自动驾驶道路车辆的六自由度昼夜视觉定位,具有预先的3D结构
在一天中的任何时间,强大而可靠的视觉定位是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,在广泛的户外照明条件下,使用由调查车辆事先收集的3D场景,在白天和晚上进行在线6自由度视觉定位。我们建议使用一维照明不变色彩空间,它源于相机和场景照明的光谱特性建模。我们将我们之前的定位与先验结构外观(LAPS)的工作与这种照明不变色彩空间结合起来,证明与使用传统的RGB色彩空间相比,我们全天定位的能力有了显着提高。我们的最终目标是实现稳健可靠的随时定位——这是道路车辆低成本自动驾驶的诱人提议。因此,我们使用一辆公路车辆在整整24小时内收集的32公里数据来演示我们的技术。
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