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：无人机在封闭环境中的自主运行需要精确且可靠的姿态估计，以便在无需GNSS等外部定位系统的情况下实现稳定控制。本研究聚焦于利用低成本轻量级激光雷达(LIDAR)生成的激光扫描数据来估计无人机姿态。我们提出了一种适用于轻量级（重量低于200克）激光雷达传感器的定位系统，该系统在现有方法失效的任意环境中均具有高可靠性。所提方法的普适性使其可部署于广泛的应用场景，并支持不同环境类型间的无缝切换。激光雷达定位的优势在于其对低光照条件的鲁棒性，这在基于摄像头的方案中通常难以应对——尤其在黑暗室内环境及室内外环境过渡场景中。我们的方法可执行照明不良的室内场所（如历史建筑、仓库）以及受限的室外环境（如森林）中的任务，这些场景中视觉方法会因场景对比度过高而失效，而大型高配无人机则因空间受限无法部署。