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liosam_mapper's Introduction

LIO-SAM Mapper

This is an offline version of LIO-SAM that produces a determenstic output, through exchanging messages/data using pointers instead of topics. It is configured to run with ouster lidar packets and pointclouds. This mapper can output different pointclouds to PCD files as well as a CSV file containing the poses at each keyframe.

Installation

Todo.

Demo

  • Download and unzip court_yard_stroll_filtered.zip.
  • Modify some parameters in param.yaml.
    • Set readBag to the path of court_yard_stroll_filtered.zip.
    • Set SaveDire to a directory where the output files could be saved.
    • Set pointCloudTopic to /os_cloud_node/points.
  • Run
roslaunch lio_sam run.launch

Parameters

Below are the additional parameters added, information about the other parameters might be found in LIO-SAM.

Parameter Type Description
readBag String Rosbag path
saveDir String Saving directory
saveToRosbag Bool Set to True to save global map and trajectory to a rosbag
saveTrajectoryCSV Bool Set to True to save trajectory to CSV
saveRawPCD Bool Set to True to save raw lidar pointclouds to PCDc (lidar frame)
saveDeskewedPCD Bool Set to True to save deskewed pointclouds to PCDs (lidar frame)
saveRegisteredCloudPCD Bool Set to True to save registered pointclouds to PCDs (map frame)
saveRegisteredFeaturesPCD Bool Set to True to save registered feature pointclouds to PCDs (map frame)
LMOMaxIterations Int Max iterations count for lidar odometry optimisation

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