2014-01-04 15:54:22 +08:00
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README - Georgia Tech Smoothing and Mapping library
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===================================================
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Quickstart
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In the root library folder execute:
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```
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#!bash
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$ mkdir build
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$ cd build
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$ cmake ..
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2014-01-04 16:15:25 +08:00
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$ make check (optional, runs unit tests)
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2014-01-04 15:54:22 +08:00
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$ make install
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```
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2014-01-04 16:15:25 +08:00
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Prerequisites:
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- [Boost](http://www.boost.org/users/download/) >= 1.43 (Ubuntu: `sudo apt-get install libboost-all-dev`)
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- [CMake](http://www.cmake.org/cmake/resources/software.html) >= 2.6 (Ubuntu: `sudo apt-get install cmake`)
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Optional prerequisites - used automatically if findable by CMake:
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- [Intel Threaded Building Blocks (TBB)](http://www.threadingbuildingblocks.org/) (Ubuntu: `sudo apt-get install libtbb-dev`)
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- [Intel Math Kernel Library (MKL)](http://software.intel.com/en-us/intel-mkl)
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Tested compilers
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- GCC 4.2-4.7
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2014-01-05 01:31:12 +08:00
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- OSX Clang 2.9-5.0
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2014-01-04 16:15:25 +08:00
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- OSX GCC 4.2
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- MSVC 2010, 2012
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Tested systems:
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- Ubuntu 11.04 - 13.10
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- MacOS 10.6 - 10.9
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- Windows 7, 8
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2014-01-05 01:31:12 +08:00
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See the `INSTALL` file for more detailed installation instructions.
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2014-01-04 15:54:22 +08:00
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What is GTSAM?
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==============
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GTSAM is a library of C++ classes that implement smoothing and
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mapping (SAM) in robotics and vision, using factor graphs and Bayes
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networks as the underlying computing paradigm rather than sparse
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2014-01-05 02:59:43 +08:00
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matrices.
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2014-01-04 15:54:22 +08:00
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2014-01-05 02:59:43 +08:00
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On top of the C++ library, GTSAM includes a MATLAB interface (enable
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GTSAM_INSTALL_MATLAB_TOOLBOX in CMake to build it). A Python interface
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is under development.
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GTSAM is open source under the BSD license, see the `LICENSE.BSD` file.
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2014-01-04 15:54:22 +08:00
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2014-01-05 01:31:12 +08:00
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Please see the `examples/` directory and the `USAGE` file for examples on how to use GTSAM.
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2014-01-04 15:54:22 +08:00
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The library is organized according to the following directory structure:
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2014-01-04 16:15:25 +08:00
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3rdparty local copies of third party libraries - Eigen3 and CCOLAMD
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base provides some base Math and data structures, as well as test-related utilities
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geometry points, poses, tensors, etc
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inference core graphical model inference such as factor graphs, junction trees, Bayes nets, Bayes trees
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linear inference specialized to Gaussian linear case, GaussianFactorGraph etc...
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nonlinear non-linear factor graphs and non-linear optimization
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slam SLAM and visual SLAM application code
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2014-01-04 15:54:22 +08:00
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This library contains unchanged copies of two third party libraries, with documentation
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of licensing as follows:
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- CCOLAMD 2.73: Tim Davis' constrained column approximate minimum degree ordering library
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- http://www.cise.ufl.edu/research/sparse
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- Licenced under LGPL v2.1, provided in gtsam/3rdparty/CCOLAMD/Doc/lesser.txt
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- Eigen 3.2: General C++ matrix and linear algebra library
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- Licenced under MPL2, provided in gtsam/3rdparty/Eigen/COPYING.README (some code that is 3rd-party to Eigen is BSD and LGPL)
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