bc094951ed
ChartValues are GenericValues and a Chart, which defaults to DefaultChart had to make charts functional (ie no storage of the chart origin) so that they could be zero sized base class otherwise there would have been a double of the memory for values (ones for the value, and once for the chart origin, which default to the same) most tests work, execept for serialization based stuff, and const filtering of values. |
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| doc | ||
| examples | ||
| gtsam | ||
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| timing | ||
| wrap | ||
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| DEVELOP | ||
| INSTALL | ||
| LICENSE | ||
| LICENSE.BSD | ||
| README.md | ||
| THANKS | ||
| USAGE | ||
| gtsam.h | ||
| gtsam_extra.cmake.in | ||
| makestats.sh | ||
| matlab.h | ||
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README.md
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)
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)
Additional Information
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.