{"id":23511140,"url":"https://github.com/maxmsun/gtsam","last_synced_at":"2025-07-30T02:05:28.516Z","repository":{"id":204936769,"uuid":"230800733","full_name":"MaxMSun/gtsam","owner":"MaxMSun","description":"gtsam branch for compiling \"https://github.com/CogRob/distributed-mapper\"","archived":false,"fork":false,"pushed_at":"2019-12-29T20:46:47.000Z","size":16136,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-13T17:19:53.006Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MaxMSun.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-12-29T20:37:49.000Z","updated_at":"2019-12-29T20:46:53.000Z","dependencies_parsed_at":null,"dependency_job_id":"75581424-2fc9-4fca-906a-27507d3cd7c0","html_url":"https://github.com/MaxMSun/gtsam","commit_stats":null,"previous_names":["muchensun/gtsam","maxmsun/gtsam"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MaxMSun/gtsam","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MaxMSun%2Fgtsam","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MaxMSun%2Fgtsam/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MaxMSun%2Fgtsam/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MaxMSun%2Fgtsam/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MaxMSun","download_url":"https://codeload.github.com/MaxMSun/gtsam/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MaxMSun%2Fgtsam/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267797320,"owners_count":24145701,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-30T02:00:09.044Z","response_time":70,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-25T12:13:30.507Z","updated_at":"2025-07-30T02:05:28.480Z","avatar_url":"https://github.com/MaxMSun.png","language":"C++","readme":"README - Georgia Tech Smoothing and Mapping library\n===================================================\n\nThis version is for the [distributed-mapper](https://github.com/CogRob/distributed-mapper) library. It's modified based on:\n\n~~~\n$ git clone https://bitbucket.org/gtborg/gtsam\n$ git checkout b7c695fa71efd43b40972eec154df265617fc07d -b dist-mapper\n~~~\n\n***\n\nWhat is GTSAM?\n--------------\n\nGTSAM is a library of C++ classes that implement smoothing and\nmapping (SAM) in robotics and vision, using factor graphs and Bayes\nnetworks as the underlying computing paradigm rather than sparse\nmatrices.\n\nOn top of the C++ library, GTSAM includes a MATLAB interface (enable\nGTSAM_INSTALL_MATLAB_TOOLBOX in CMake to build it). A Python interface\nis under development.\n\nQuickstart\n----------\n\nIn the root library folder execute:\n\n```\n#!bash\n$ mkdir build\n$ cd build\n$ cmake ..\n$ make check (optional, runs unit tests)\n$ make install\n```\n\nPrerequisites:\n\n- [Boost](http://www.boost.org/users/download/) \u003e= 1.43 (Ubuntu: `sudo apt-get install libboost-all-dev`)\n- [CMake](http://www.cmake.org/cmake/resources/software.html) \u003e= 2.6 (Ubuntu: `sudo apt-get install cmake`)\n- A modern compiler, i.e., at least gcc 4.7.3 on Linux.\n\nOptional prerequisites - used automatically if findable by CMake:\n\n- [Intel Threaded Building Blocks (TBB)](http://www.threadingbuildingblocks.org/) (Ubuntu: `sudo apt-get install libtbb-dev`)\n- [Intel Math Kernel Library (MKL)](http://software.intel.com/en-us/intel-mkl)\n\nGTSAM 4 Compatibility\n---------------------\n\nGTSAM 4 will introduce several new features, most notably Expressions and a python toolbox. We will also deprecate some legacy functionality and wrongly named methods, but by default the flag GTSAM_ALLOW_DEPRECATED_SINCE_V4 is enabled, allowing anyone to just pull V4 and compile. To build the python toolbox, however, you will have to explicitly disable that flag.\n\nAlso, GTSAM 4 introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we will also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 will be deprecated, so please be aware that this might render functions using their default constructor incorrect.\n\nThe Preintegrated IMU Factor\n----------------------------\n\nGTSAM includes a state of the art IMU handling scheme based on\n\n- Todd Lupton and Salah Sukkarieh, \"Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions\", TRO, 28(1):61-76, 2012.\n\nOur implementation improves on this using integration on the manifold, as detailed in\n\n- Luca Carlone, Zsolt Kira, Chris Beall, Vadim Indelman, and Frank Dellaert, \"Eliminating conditionally independent sets in factor graphs: a unifying perspective based on smart factors\", Int. Conf. on Robotics and Automation (ICRA), 2014. \n- Christian Forster, Luca Carlone, Frank Dellaert, and Davide Scaramuzza, \"IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation\", Robotics: Science and Systems (RSS), 2015.\n\nIf you are using the factor in academic work, please cite the publications above.\n\nIn GTSAM 4 a new and more efficient implementation, based on integrating on the NavState tangent space and detailed in docs/ImuFactor.pdf, is enabled by default. To switch to the RSS 2015 version, set the flag **GTSAM_TANGENT_PREINTEGRATION** to OFF.\n\n\n\nAdditional Information\n----------------------\n\nRead about important [`GTSAM-Concepts`](GTSAM-Concepts.md) here.\n\nSee the [`INSTALL`](INSTALL) file for more detailed installation instructions.\n\nGTSAM is open source under the BSD license, see the [`LICENSE`](LICENSE) and [`LICENSE.BSD`](LICENSE.BSD) files.\n\nPlease see the [`examples/`](examples) directory and the [`USAGE`](USAGE.md) file for examples on how to use GTSAM.\n\nGTSAM was developed in the lab of [Frank Dellaert](http://www.cc.gatech.edu/~dellaert) at the [Georgia Institute of Technology](http://www.gatech.edu), with the help of many contributors over the years, see [THANKS](THANKS).","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmaxmsun%2Fgtsam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmaxmsun%2Fgtsam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmaxmsun%2Fgtsam/lists"}