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A general and flexible factor graph non-linear least square optimization framework
A graph-based multi-sensor fusion framework. It can be used to fuse various relative or absolute measurments with IMU readings in real-time.
A collection of GTSAM factors and optimizers for point cloud SLAM
Factor graphs and loopy belief propagation implemented in Python
Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
Factored inference for discrete-continuous smoothing and mapping.
Robust GNSS Processing With Factor Graphs
Lightweighted graph optimization (Factor graph) library.
Official repo for the paper "SAGE: SLAM with Appearance and Geometry Prior for Endoscopy" (ICRA 2022)
State Estimation for SLAM: Filter(EKF, Particle Filter), MAP(GN, LM), Solver(Ceres-Solver, G2O, GTSAM), Bundle Adjustment
A novel architecture in which the Factor Graph Optimization (FGO) is hybrid with the Extended Kalman Filter (EKF) for tightly coupled GNSS/UWB integration with online Temporal calibration (FE-GUT).
Software Release for "Incremental Covariance Estimation for Robust Localization"
Code release for "Evaluation of Precise Point Positioning Convergence with an Incremental Graph Optimizer".
Belief propagation with sparse matrices (scipy.sparse) in Python for LDPC codes. Includes NumPy implementation of message passing (min-sum and sum-product) and a few other decoders.
General purpose C++ library for managing discrete factor graphs
The algorithm solves the DC state estimation problem in electric power systems using the Gaussian belief propagation over factor graphs.
The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm.