DLL: Direct LIDAR Localization. A map-based localization approach for aerial robots

TL;DR

DLL is a fast, featureless, map-based LIDAR localization method for aerial robots that refines pose estimates efficiently and robustly, outperforming Monte-Carlo methods in speed and comparable to other optimization techniques in accuracy.

Contribution

The paper introduces DLL, a novel direct LIDAR localization approach that does not rely on feature extraction or point correspondences, enabling faster and robust pose tracking for aerial robots.

Findings

DLL outperforms Monte-Carlo localization in speed.

DLL achieves comparable accuracy to other optimization methods.

DLL is robust to odometric errors.

Abstract

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.