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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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
CONTRIBUTING
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 | |
macOS | clang | |
Windows | MSVC |
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:
-
Intel Threaded Building Blocks (TBB) (Ubuntu:
sudo apt-get install libtbb-dev
) -
Intel Math Kernel Library (MKL) (Ubuntu: installing using APT)
- See INSTALL.md for more installation information
- Note that MKL may not provide a speedup in all cases. Make sure to benchmark your problem with and without MKL.
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