This paper presents DLL, a fast 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.
@article{arxiv.2103.06112,
title = {DLL: Direct LIDAR Localization. A map-based localization approach for aerial robots},
author = {Fernando Caballero and Luis Merino},
journal= {arXiv preprint arXiv:2103.06112},
year = {2021}
}
Comments
Accepted for IROS2021. Associated code can be downloaded from https://github.com/robotics-upo/dll