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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].

lol

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
  1. 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

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