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.

| CI Status | Platform | Compiler | |:———-|:———|:———| | | Ubuntu 22.04, MacOS 13-14, Windows | gcc/clang,MSVC | | | Latest Windows/Ubuntu/Mac | - | | | See pypi files; no Windows| - |

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 all unit tests
make install

Prerequisites:

• A modern compiler:
  • Mac: at least xcode-14.2
  • Linux: at least clang-11 or gcc-9
  • Windows: at least msvc-14.2
• CMake >= 3.9
  • Ubuntu: sudo apt-get install cmake

Optional Boost prerequisite:

Boost is now optional. Two cmake flags govern its behavior:

• GTSAM_USE_BOOST_FEATURES = ON|OFF: some of our timers and concept checking in the tests still depend on boost.
• GTSAM_ENABLE_BOOST_SERIALIZATION = ON|OFF: serialization of factor graphs, factors, etc still is done using boost

If one or both of these flags are ON, you need to install Boost >= 1.70 - Mac: brew install boost - Ubuntu: sudo apt-get install libboost-all-dev - Windows: We highly recommend using the vcpkg package manager. For other installation methods or troubleshooting, please see the guidance in the cmake/HandleBoost.cmake script.

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:

```bibtex @book{factor_graphs_for_robot_perception, author={Frank Dellaert and Michael Kaess}, year={2017}, title={Factor Graphs for Robot Perception},

File truncated at 100 lines see the full file