A collection of GTSAM factors and optimizers for point cloud SLAM

General factor graph solver in rust and python

Factored inference for discrete-continuous smoothing and mapping.

Pure python implementation of minisam.

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).

Pratice and example to solve the pose graph SLAM problem using GTSAM

General purpose C++ library for managing discrete factor graphs

A graph-based multi-sensor fusion framework. It can be used to fuse various relative or absolute measurments with IMU readings in real-time.

Master thesis

Developed and implemented 2D and 3D Pose Graph SLAM using the GTSAM library and Gauss Newton Solver on the Intel and Parking Garage g2o datasets respectively

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.

Implementation of the Belief Propagation Side Channel Attack

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

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.

Factor graphs and loopy belief propagation implemented in Python

深蓝学院多传感器融合定位 Implementation of Multi-sensor Fusion SLAM Algorithms

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.

A general and flexible factor graph non-linear least square optimization framework

Experimental platform to achieve fused environment perception using different modalities of sensors