G2O: General framework for graph optomization
An open-source C++ framework for optimizing graph-based nonlinear error functions, widely used in robotics and computer vision.
What is G2O: General framework for graph optomization?
g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions, commonly used in robotics and computer vision. It solves nonlinear least squares problems by representing them as graphs and finding parameter configurations that best explain noisy measurements. The framework is extensible and provides efficient solutions for tasks like simultaneous localization and mapping (SLAM) and bundle adjustment (BA).
Researchers and engineers in robotics and computer vision who need to solve graph-based optimization problems, such as SLAM or bundle adjustment, with a flexible and high-performance C++ library.
Developers choose g2o for its extensibility, allowing new problems to be defined in just a few lines of code, and its performance, which matches specialized state-of-the-art implementations. Its general framework design supports a wide range of applications beyond specific use cases.
Overview
g2o: A General Framework for Graph Optimization
Use Cases
Best For
- Implementing simultaneous localization and mapping (SLAM) in robotics
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