This paper presents DLL, a direct map-based localization technique using 3D LIDAR for its application to aerial robots. DLL implements a point cloud to map registration based on non-linear optimization of the distance of the points and the map, thus not requiring features, neither point correspondences. Given an initial pose, the method is able to track the pose of the robot by refining the predicted pose from odometry. Through benchmarks using real datasets and simulations, we show how the method performs much better than Monte-Carlo localization methods and achieves comparable precision to other optimization-based approaches but running one order of magnitude faster. The method is also robust under odometric errors. The approach has been implemented under the Robot Operating System (ROS), and it is publicly available.
翻译:本文展示了DLL, 这是一种直接基于地图的定位技术, 使用 3D LIDAR 进行航空机器人应用。 DLL 使用一个点云, 在非线性优化点和地图距离的基础上进行地图登记, 因而不需要特征, 也不需要点对应。 鉴于最初的外观, 该方法能够通过对odo测量预测的外观进行精炼来跟踪机器人的外观。 通过使用真实的数据集和模拟, 我们展示了该方法如何比 Monte- Carlo 本地化方法要好得多, 并实现了与其他优化方法相似的精确度, 但运行速度要快一个级。 该方法在odoricat 错误下也很有力。 该方法已在机器人操作系统(ROS)下实施, 并且可以公开使用。