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A Scan Context-enabled LiDAR SLAM Using Factor Graph-Based Optimization.

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SCL-SLAM

A Scan Context-enabled LiDAR SLAM Using Factor Graph-Based Optimization.

Prerequisites

  • CMake (compilation configuration tool)
sudo apt-get install cmake
  • Boost (portable C++ source libraries)
sudo apt-get install libboost-all-dev
  • GTSAM (Georgia Tech Smoothing and Mapping library)

Install during the compilation.

Install during the compilation.

  • Python (required system packages)
sudo apt-get install python-wstool python-catkin-tools

Compilation

Set up the workspace configuration:

mkdir -p ~/scl_slam_ws/src
cd ~/scl_slam_ws
catkin init
catkin config --merge-devel
catkin config --cmake-args -DCMAKE_BUILD_TYPE=Release

Then use wstool for fetching catkin dependencies:

cd src
git clone https://github.com/thisparticle/scl_slam.git
git clone https://github.com/thisparticle/fast-lio.git
wstool init
wstool merge dlc-slam/dependencies.rosinstall
wstool update

Build

catkin build dlc_fast_lio

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A Scan Context-enabled LiDAR SLAM Using Factor Graph-Based Optimization.

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