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A general and flexible factor graph non-linear least square optimization framework
| Date | Stars |
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| 2026-07-24 | 515 |
| 2026-07-25 | 515 |
| 2026-07-28 | 515 |
| 2026-07-30 | 515 |
| 2026-08-06 | 515 |
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miniSAM ===== Website: https://minisam.readthedocs.io/ ------------------------------------------- miniSAM is an open-source C++/Python framework for solving factor graph based least squares problems. The APIs and implementation of miniSAM are heavily inspired and influenced by [GTSAM](https://gtsam.org/), a famous factor graph framework, but miniSAM is a much more lightweight framework with - Full Python/NumPy API, which enables more agile development and easy binding with existing Python projects, and - A wide list of sparse linear solvers, including CUDA enabled sparse linear solvers. miniSAM is developed by [Jing Dong](mailto:[email protected]) and [Zhaoyang Lv](mailto:[email protected]). This work was initially started as final project of [Math 6644](https://www.cc.gatech.edu/~echow/cse6644-17.html) back to 2017, and mostly finished part-time when both authors were PhD students at College of Computing, Georgia Institute of Technology. Mandatory Prerequisites ------ - [CMake](https://cmake.org/) 3.4+ (Ubuntu: `sudo apt-get install cmake`), compilation configuration tool. - [Eigen](http://eigen.tuxfamily.org) 3.3.0+ (Ubuntu: `sudo apt-get install libeigen3-dev`), a C++ template library for linear algebra. Optional Dependencies ------ - [Sophus](https://github.com/strasdat/Sophus), a C++ implementation of Lie Groups using Eigen. miniSAM uses Sophus for all SLAM/multi-view geometry functionalities. - [Python](http://www.python.org/) 2.7/3.4+ to use miniSAM Python package. - [SuiteSparse](http://faculty.cse.tamu.edu/davis/suitesparse.html) (Ubuntu: `sudo apt-get install libsuitesparse-dev`), a suite of sparse matrix algorithms. miniSAM has option to use CHOLMOD and SPQR sparse linear solvers. - [CUDA](https://developer.nvidia.com/cuda-downloads) 9.0+. miniSAM has option to use cuSOLVER Cholesky sparse linear solver. Get Started ------ Please refer to https://minisam.readthedocs.io/install.html for more details. To get and compile the library (on Ubuntu Linux): ``` $ git clone --recurse-submodules https://github.com/dongjing3309/minisam.git $ mkdir build $ cd build $ cmake .. $ make $ make check # optional, run unit tests ``` Tested Compatibility ----- The miniSAM library is designed to be cross-platform, should be compatible with any modern compiler which supports C++11. It has been tested on Ubuntu Linux and Windows for now. - Ubuntu: GCC 5.4+, Clang 3.8+ - Windows: Visual C++ 2015.3+ Questions & Bug Reporting ----- Please use Github issue tracker for general questions and reporting bugs, before submitting an issue please have a look of [this page](https://minisam.readthedocs.io/github_issue.html). Citing ----- If you use miniSAM in an academic context, please cite following publications: ``` @article{Dong19ppniv, author = {Jing Dong and Zhaoyang Lv}, title = {mini{SAM}: A Flexible Factor Graph Non-linear Least Squares Optimization Framework}, journal = {CoRR}, volume = {abs/1909.00903}, year = {2019}, url = {http://arxiv.org/abs/1909.00903} } ``` License ----- miniSAM is released under the BSD license, reproduced in the file LICENSE in this directory. Note that the linked sparse linear solvers have different licenses, see [this page](https://minisam.readthedocs.io/install.html#sparse-solvers-license) for details
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matched fp:b9162fd435641779, topic:robotics, topic:slam, readme:slam