g2o: A General Framework for Graph Optimization
-
Updated
Jun 23, 2024 - C++
g2o: A General Framework for Graph Optimization
Python binding of SLAM graph optimization framework g2o
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
A simple monocular visual odometry (part of vSLAM) by ORB keypoints with initialization, tracking, local map and bundle adjustment. (WARNING: Hi, I'm sorry that this project is tuned for course demo, not for real world applications !!!)
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
A CUDA implementation of Bundle Adjustment
A exercise of BA, ubuntu20, opencv4+, eigen3.3.7+
Python implementation of Graph SLAM
A .Net wrapper for the G2O (graph-based optimization) library
Basic Sparse-Cholesky Graph SLAM solver implemented in python
A simple slimmed down mono slam implementation
LIDAR SLAM for Autonomous Vehicles Playground
This repo contains several concepts and implimentations of computer vision and visual slam algorithms for rapid prototyping for reserachers to test concepts.
Add a description, image, and links to the g2o topic page so that developers can more easily learn about it.
To associate your repository with the g2o topic, visit your repo's landing page and select "manage topics."