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CppUnitLite | ||
cmake | ||
doc | ||
examples | ||
gtsam | ||
gtsam_unstable | ||
matlab | ||
package_scripts | ||
tests | ||
wrap | ||
.cproject | ||
.gitignore | ||
.project | ||
CMakeLists.txt | ||
LICENSE | ||
LICENSE.BSD | ||
README | ||
README.md | ||
THANKS | ||
USAGE | ||
gtsam.h | ||
gtsam_extra.cmake.in | ||
makestats.sh | ||
matlab.h |
README.md
README - Georgia Tech Smoothing and Mapping library
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
)
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)
Tested compilers
- GCC 4.2-4.7
- OSX Clang 2.9-5.0
- OSX GCC 4.2
- MSVC 2010, 2012
Tested systems:
- Ubuntu 11.04 - 13.10
- MacOS 10.6 - 10.9
- Windows 7, 8
See the INSTALL
file for more detailed installation instructions.
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.
GTSAM is open source under the BSD license, see the LICENSE.BSD
file.
Please see the examples/
directory and the USAGE
file for examples on how to use GTSAM.
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
This library contains unchanged copies of two third party libraries, with documentation of licensing as follows:
- CCOLAMD 2.73: Tim Davis' constrained column approximate minimum degree ordering library
- http://www.cise.ufl.edu/research/sparse
- Licenced under LGPL v2.1, provided in gtsam/3rdparty/CCOLAMD/Doc/lesser.txt
- Eigen 3.2: General C++ matrix and linear algebra library
- Licenced under MPL2, provided in gtsam/3rdparty/Eigen/COPYING.README (some code that is 3rd-party to Eigen is BSD and LGPL)