Autonomous operation of UAVs in a closed environment requires precise and reliable pose estimate that can stabilize the UAV without using external localization systems such as GNSS. In this work, we are concerned with estimating the pose from laser scans generated by an inexpensive and lightweight LIDAR. We propose a localization system for lightweight (under 200g) LIDAR sensors with high reliability in arbitrary environments, where other methods fail. The general nature of the proposed method allows deployment in wide array of applications. Moreover, seamless transitioning between different kinds of environments is possible. The advantage of LIDAR localization is that it is robust to poor illumination, which is often challenging for camera-based solutions in dark indoor environments and in the case of the transition between indoor and outdoor environment. Our approach allows executing tasks in poorly-illuminated indoor locations such as historic buildings and warehouses, as well as in the tight outdoor environment, such as forest, where vision-based approaches fail due to large contrast of the scene, and where large well-equipped UAVs cannot be deployed due to the constrained space.
翻译:在封闭环境中自动操作无人驾驶航空器需要准确和可靠的表面估计,这种估计可以稳定无人驾驶航空器,而不必使用全球导航卫星系统等外部定位系统。在这项工作中,我们关心的是估计由廉价和轻便LIDAR产生的激光扫描所产生形状。我们提议为在任意环境中高可靠性的轻型(200克以下)LIDAR传感器建立一个本地化系统,在任意环境中,其他方法都失败。拟议方法的一般性质允许广泛部署各种应用。此外,不同环境之间的无缝过渡是可能的。LIDAR的优势在于它能够对贫乏的照明进行稳健,因为在黑暗的室内环境中和在室内与室外环境之间的过渡中,对基于相机的解决方案往往具有挑战性。我们的方法允许在历史建筑和仓库等低污染的室内地点以及在紧密室环境(如森林)执行任务,在那里,基于愿景的方法由于场景大反常,而且由于空间受限制而无法部署大型设备齐全的无人驾驶飞行器。