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A Modular Framework for LiDAR-based Lifelong Mapping

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LT-mapper (ICRA 22)

What is LT-mapper?

  • A Modular Framework for LiDAR-based Lifelong Mapping

Why LT-mapper?

  • For LiDAR-based long-term mapping, three challenges exist.

Features

  • TBA

How to use?

Prerequisites

  • TBA

build

  • TBA

Tutorial and examples

0. Single-session Data Generation

  • Using the saver provided with SC-LIO-SAM (also in SC-A-LOAM or FAST_LIO_SLAM), a user should generate the set of sesssion data (i.e., keyframe point cloud scans, keyframe scan context descriptors (SCDs), and an initial pose-graph text file) for each session.

1. LT-SLAM

  • Tutorial video

  • command

      # change the paths in ltslam/config/params.yaml
      roslaunch ltslam run.launch
    

2. LT-removert and LT-map

  • ltremovert directory runs removert (for single-session cleaning) and change detection between two sessions.
  • command
      TBA
    
  • Outputs

LT-mapper ParkingLot dataset

Citation

@INPROCEEDINGS { kim2021ltmapper,
    AUTHOR = { Giseop Kim, Ayoung Kim },
    TITLE = { {LT-mapper: A Modular Framework for LiDAR-based Lifelong Mapping} },
    BOOKTITLE = { Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) },
    YEAR = { 2022 },
}

Contact

  • Maintained by Giseop Kim and please contact the author via giseop.kim@naverlabs.com

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