README - Georgia Tech Smoothing and Mapping library

What is GTSAM?

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

On top of the C++ library, GTSAM includes a MATLAB interface (enable GTSAM_INSTALL_MATLAB_TOOLBOX in CMake to build it). A Python interface is under development.

Quickstart

In the root library folder execute:

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

Prerequisites:

• Boost >= 1.43 (Ubuntu: sudo apt-get install libboost-all-dev)
• CMake >= 2.6 (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)

GTSAM 4 Compatibility

GTSAM 4 will introduce several new features, most notably Expressions and a python toolbox. We will also deprecate some legacy functionality and wrongly named methods, but by default the flag GTSAM_ALLOW_DEPRECATED_SINCE_V4 is enabled, allowing anyone to just pull V4 and compile. To build the python toolbox, however, you will have to explicitly disable that flag.

Also, GTSAM 4 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 will also do.

Additional Information

Read about important GTSAM-Concepts here.

See the INSTALL file for more detailed installation instructions.

GTSAM is open source under the BSD license, see the LICENSE and LICENSE.BSD files.

Please see the examples/ directory and the USAGE file for examples on how to use GTSAM.

GTSAM was developed in the lab of Frank Dellaert at the Georgia Institute of Technology, with the help of many contributors over the years, see THANKS.