LOL

Laser Odometry and Localization

Introduction

Add localization support for LOAM/LeGO-LOAM, referenced from 8.2.3 Localization and Map Merging in [1].

Compared to the previous section, the difference is that the localization does not process individual scans but stacks a number of scans for batch processing. Thanks to the high-accuracy
odometry estimation, scans are registered precisely in a local coordinate frame where drift is
negligible over a short period of time (a few seconds).

Localization test(running at TX2) under point cloud map built by A-LeGO-LOAM[2].

Map bulit by lol using corner point cloud.

Usage

Input

• /surf: surf point cloud extracted by Laser Odometry
• /corner: corner point cloud extracted by Laser Odometry
• /outlier: outlier point cloud extracted by Image Projection
• /odom/lidar: odometry estimeted by Laser Odometry
• global map pcd file: built by A-LeGO-LOAM

Output

• /tf: map -> odom
• /currenct_pose: PoseStamped
• …

Run the Package

1. Run the launch file:

   roslaunch lol lol.launch

2. Play existing bag files test_0515.bag:

   rosbag play test_0515.bag --clock --topics /lslidar_point_cloud

Reference

1. Zhang J. Online Lidar and Vision based Ego-motion Estimation and Mapping[D]. , 2015.
2. https://github.com/jyakaranda/A-LeGO-LOAM