Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
Repo symbol

lvr2 repository

lvr2

ROS Distro
jazzy

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro kilted showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro rolling showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro ardent showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro bouncy showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro crystal showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro eloquent showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro dashing showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro galactic showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro foxy showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro iron showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro lunar showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro jade showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro indigo showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro hydro showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

         /\
        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
No version for distro kinetic showing humble. Known supported distros are highlighted in the buttons above.
Repo symbol

lvr2 repository

lvr2

ROS Distro
humble

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version main
Last Updated 2026-01-23
Dev Status DEVELOPED
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 25.2.1

README

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        /  \               ##          ##      ##    #######         ######
       /    \              ##          ##      ##    ##     ##     ##      ##
      /      \             ##           ##    ##     ##      ##            ##
     /________\            ##           ##    ##     ##     ##            ##
    /\        /\           ##            ##  ##      #######             ##
   /  \      /  \          ##            ##  ##      ##    ##          ##
  /    \    /    \         ##             ####       ##     ##       ##
 /      \  /      \        ##########      ##        ##      ##    ##########
/________\/________\

About

This library delivers tools to build surface reconstructions from point cloud data. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate algorithms for surface reconstruction with a strong focus on robotic applications such as autonomous navigation and localization in complex environments.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2 - develop

Linux (Ubuntu 18.04, 20.04, 22.04, 24.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev \
     libembree-dev

A C++17 compiler is required.

Optional for NVIDIA graphics cards users

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site. To enable CUDA support, you need to compile the software with a compatible GCC version. All compatibilities are listed in CMakeModules/max_cuda_gcc_version.cmake.

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

You can experiment with the software using the the example dataset scan.pts from the dat folder. For a simple reconstruction call in your build directory:

bin/lvr2_reconstruct ../dat/scan.pts

Output: ```bash /\ / \ ## ## ## ####### ###### / \ ## ## ## ## ## ## ## / \ ## ## ## ## ## ## /________\ ## ## ## ## ## ## /\ /\ ## ## ## ####### ## / \ / \ ## ## ## ## ## ## / \ / \ ## #### ## ## ## / \ / \ ########## ## ## ## ########## /________\/________\ ##### Program options: ##### Transform input data : NO ##### Voxelsize : 10 ##### Number of threads : 16 ##### Point cloud manager : LVR2 ##### Normal Estimation: : 0 ##### Voxel decomposition: : PMC ##### Classifier: : GREY File truncated at 100 lines [see the full file](https://github.com/uos/lvr2/tree/main/README.md)
Repo symbol

lvr2 repository

lvr2

ROS Distro
melodic

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version master
Last Updated 2021-10-08
Dev Status DEVELOPED
Released RELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 20.11.3

README

About

This software delivers tools to build surface reconstructions from point cloud data and a simple viewer to display the results. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate surface extraction algorithms for robotic applications such as tele operation in unknown environments and localization.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2

Linux (Ubuntu 18.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev

A C++17 compiler is required, e.g., g++7, gcc7 need bo installed. If CUDA is installed you also need g++6, see “Optional for NVIDIA graphics cards users”

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

Optional for NVIDIA graphics cards users:

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site:

To enable CUDA support, you need to compile the software with a compatible GCC version. We have testet compilation with CUDA 9.1 and GCC 6. To use this compiler for compilation of CUDA generated code, set the CUDA_HOST_COMPILER option to g++-6 is forced to g++-6. Please ensure that this version is installed on your system. /

Step 3: Installation

After successful compilation, you will find the generated example tools in the ./bin/ directory. Optionally, you can install the library and header files to your system:

sudo make install

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

Your can experiment with the software using the provided dataset. For a simple reconstruction call in yout build directory:

bin/lvr2_reconstruct ../dat/scan.pts

in the root directory of the project. This will create a file called “triangle_mesh.ply” which can be displayed using the viewer application:

bin/lvr2_viewer triangle_mesh.ply

For more information, build the Doxygen documentation by calling

make doc

in the build directory.

Repo symbol

lvr2 repository

lvr2

ROS Distro
noetic

Repository Summary

Checkout URI https://github.com/uos/lvr2.git
VCS Type git
VCS Version master
Last Updated 2021-10-08
Dev Status DEVELOPED
Released RELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
lvr2 20.11.3

README

About

This software delivers tools to build surface reconstructions from point cloud data and a simple viewer to display the results. Additionally, the found surfaces will be classified into predefined categories. The main aim of this project is to deliver fast and accurate surface extraction algorithms for robotic applications such as tele operation in unknown environments and localization.

Download and Compilation from Source

Step 0: Get the source code from our Github repository:

https://github.com/uos/lvr2

Linux (Ubuntu 18.04)

Step 1: Install all required package dependencies:

sudo apt-get install build-essential \
     cmake cmake-curses-gui libflann-dev \
     libgsl-dev libeigen3-dev libopenmpi-dev \
     openmpi-bin opencl-c-headers ocl-icd-opencl-dev \
     libvtk7-dev libvtk7-qt-dev libboost-all-dev \
     freeglut3-dev libhdf5-dev qtbase5-dev \
     qt5-default libqt5opengl5-dev liblz4-dev \
     libopencv-dev libyaml-cpp-dev

A C++17 compiler is required, e.g., g++7, gcc7 need bo installed. If CUDA is installed you also need g++6, see “Optional for NVIDIA graphics cards users”

Step 2: Configure and build from sources:

mkdir build
cd build
cmake .. && make

Optional for NVIDIA graphics cards users:

If you want to compile with CUDA support install the latest version of the CUDA toolkit, which you can find on NVIDIAs CUDA download site:

To enable CUDA support, you need to compile the software with a compatible GCC version. We have testet compilation with CUDA 9.1 and GCC 6. To use this compiler for compilation of CUDA generated code, set the CUDA_HOST_COMPILER option to g++-6 is forced to g++-6. Please ensure that this version is installed on your system. /

Step 3: Installation

After successful compilation, you will find the generated example tools in the ./bin/ directory. Optionally, you can install the library and header files to your system:

sudo make install

MacOS

Install the required libraries using Homebrew:

brew install boost boost-mpi cmake eigen flann gcc glew gsl hdf5 opencv lz4 qt vtk 

mkdir build
cd build
cmake .. && make

Usage

Your can experiment with the software using the provided dataset. For a simple reconstruction call in yout build directory:

bin/lvr2_reconstruct ../dat/scan.pts

in the root directory of the project. This will create a file called “triangle_mesh.ply” which can be displayed using the viewer application:

bin/lvr2_viewer triangle_mesh.ply

For more information, build the Doxygen documentation by calling

make doc

in the build directory.