Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file

Repo symbol

gtsam repository

gtsam

Repository Summary

Checkout URI https://github.com/borglab/gtsam.git
VCS Type git
VCS Version develop
Last Updated 2025-06-13
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
gtsam 4.3.0

README

GTSAM: Georgia Tech Smoothing and Mapping Library

Important Note

As of January 2023, the develop branch is officially in “Pre 4.3” mode. We envision several API-breaking changes as we switch to C++17 and away from boost.

In addition, features deprecated in 4.2 will be removed. Please use the stable 4.2 release if you need those features. However, most are easily converted and can be tracked down (in 4.2) by disabling the cmake flag GTSAM_ALLOW_DEPRECATED_SINCE_V42.

What is GTSAM?

GTSAM is a C++ library that implements smoothing and mapping (SAM) in robotics and vision, using Factor Graphs and Bayes Networks as the underlying computing paradigm rather than sparse matrices.

The current support matrix is:

Platform Compiler Build Status
Ubuntu 22.04/24.04 gcc/clang Linux CI
macOS clang macOS CI
Windows MSVC Windows CI

On top of the C++ library, GTSAM includes wrappers for MATLAB & Python.

Quickstart

In the root library folder execute:

#!bash
mkdir build
cd build
cmake ..
make check (optional, runs unit tests)
make install

Prerequisites:

  • Boost >= 1.65 (Ubuntu: sudo apt-get install libboost-all-dev)
  • CMake >= 3.0 (Ubuntu: sudo apt-get install cmake)
  • A modern compiler, i.e., at least gcc 4.7.3 on Linux.

Optional prerequisites - used automatically if findable by CMake:

GTSAM 4 Compatibility

GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.

There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V43 for newly deprecated methods since the 4.3 release, which is on by default, allowing anyone to just pull version 4.3 and compile.

Wrappers

We provide support for MATLAB and Python wrappers for GTSAM. Please refer to the linked documents for more details.

Citation

If you are using GTSAM for academic work, please use the following citation:

@software{gtsam,
  author       = {Frank Dellaert and GTSAM Contributors},
  title        = {borglab/gtsam},
  month        = May,
  year         = 2022,
  publisher    = {Georgia Tech Borg Lab},
  version      = {4.2a8},
  doi          = {10.5281/zenodo.5794541},
  url          = {https://github.com/borglab/gtsam)}}
}

To cite the Factor Graphs for Robot Perception book, please use:

@book{factor_graphs_for_robot_perception,
    author={Frank Dellaert and Michael Kaess},
    year={2017},
    title={Factor Graphs for Robot Perception},
    publisher={Foundations and Trends in Robotics, Vol. 6},
    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
}

If you are using the IMU preintegration scheme, please cite:

@book{imu_preintegration,
    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
    year={2015}
}

File truncated at 100 lines see the full file