GTSAM Insights

What is GTSAM?

GTSAM (Georgia Tech Smoothing and Mapping library) is a C++ library that implements factor graphs and Bayesian networks using efficient sparse matrix methods. It is widely used in robotics, computer vision, and related fields for solving estimation problems, such as simultaneous localization and mapping (SLAM), structure from motion, and sensor fusion. GTSAM provides a powerful and flexible framework for representing and solving complex probabilistic models.

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What other technologies are related to GTSAM?

GTSAM Competitor Technologies

g2o

g2o is a general graph optimization framework, similar to GTSAM, used for solving optimization problems in robotics and computer vision. It provides an alternative implementation for similar functionalities.

mentioned alongside GTSAM in 65% (91) of relevant job posts

Ceres

Ceres Solver is a library for solving large-scale optimization problems, particularly nonlinear least squares problems. It is an alternative to GTSAM for similar applications like bundle adjustment and SLAM.

mentioned alongside GTSAM in 11% (88) of relevant job posts

GTSAM Complementary Technologies

ROS

ROS (Robot Operating System) is a framework for robot software development. GTSAM can be integrated into ROS-based systems for tasks like robot localization and mapping.

mentioned alongside GTSAM in 0% (71) of relevant job posts

OpenCV

OpenCV is a library for computer vision tasks. GTSAM can be used in conjunction with OpenCV for tasks such as visual SLAM or structure from motion, using OpenCV for feature extraction and GTSAM for optimization.

mentioned alongside GTSAM in 0% (69) of relevant job posts

Python

Python is commonly used for scripting and prototyping in robotics. GTSAM can be used from Python through bindings, making it a complementary technology for development and experimentation.

mentioned alongside GTSAM in 0% (110) of relevant job posts