g2o: A General Framework for Graph Optimization
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Updated
Sep 7, 2026 - C++
g2o: A General Framework for Graph Optimization
Python binding of SLAM graph optimization framework g2o
Educational/research monocular visual odometry implementation with ORB features, initialization, tracking, local mapping, and bundle adjustment in C++.
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
A CUDA implementation of Bundle Adjustment
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
Python implementation of Graph SLAM
A simple slimmed down mono slam implementation
A exercise of BA, ubuntu20, opencv4+, eigen3.3.7+
ROS 2 underwater localization for real AUV/ROV data, validated on public ocean datasets.
A .Net wrapper for the G2O (graph-based optimization) library
This repo contains several concepts and implimentations of computer vision and visual slam algorithms for rapid prototyping for reserachers to test concepts.
A ROS package for 2-D pose graph SLAM using open karto package for the front-end and g2o solver for the back-end.
Simple implementation of Stereo SLAM system on KITTI dataset using Dense feature sampling and 3D-2D PnP localization, loop closure and g2o pose graph optimization.
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