gtsam 4.1.1
Here is a list of all modules:
[detail level 12]
 Solving of sparse linear systems with least-squaresDensely partially eliminate with Cholesky factorization
 Solving by multifrontal variable elimination (QR and Cholesky)An EliminatableClusterTree, i.e., a set of variable clusters with factors, arranged in a tree, with the additional property that it represents the clique tree associated with a Bayes net
 Solving by sequential variable elimination (QR and Cholesky)
 BaseFastMap is a thin wrapper around std::map that uses the boost fast_pool_allocator instead of the default STL allocator
 GeometryCommon base class for all calibration models
 NavigationBase class for prior on attitude Example:
 SLAMPreintegratedCombinedMeasurements integrates the IMU measurements (rotation rates and accelerations) and the corresponding covariance matrix
 NonlinearCustom factor that takes a std::function as the error
 ISAM2Implementation of the full ISAM2 algorithm for incremental nonlinear optimization
 SAMBinary factor for a bearing measurement Works for any two types A1,A2 for which the functor Bearing<A1,A2>() is defined
 SFMThe MFAS class to solve a Minimum feedback arc set (MFAS) problem