What is this file?
This file explains how to make use of the library for common SLAM tasks, using a visual SLAM implementation as an example.
Install: Follow the installation instructions in the README file to build and install gtsam, as well as running tests to ensure the library is working properly.
Compiling/Linking with gtsam: The installation creates a binary "libgtsam" at the installation prefix, and an include folder "gtsam". These are the only required includes, but the library has also been designed to make use of XML serialization through the Boost.serialization library, which requires the the Boost.serialization headers and binaries to be linked.
If you use CMake for your project, you can use the CMake scripts in the cmake folder for finding GTSAM, CppUnitLite, and Wrap.
Examples: To see how the library works, examine the unit tests provided.
The GTSAM library has three primary components necessary for the construction of factor graph representation and optimization which users will need to adapt to their particular problem.
The library is organized according to the following directory structure:
3rdparty local copies of third party libraries - Eigen3 and CCOLAMD base provides some base Math and data structures, as well as test-related utilities geometry points, poses, tensors, etc inference core graphical model inference such as factor graphs, junction trees, Bayes nets, Bayes trees linear inference specialized to Gaussian linear case, GaussianFactorGraph etc... nonlinear non-linear factor graphs and non-linear optimization slam SLAM and visual SLAM application code