leggedrobotics/holistic_fusion

The fuse stack provides a general architecture for performing sensor fusion live on a robot. Some possible applications include state estimation, localization, mapping, and calibration.

An optimization-based multi-sensor state estimator

A Modular Optimization framework for Localization and mApping (MOLA)

robot_localization is a package of nonlinear state estimation nodes. The package was developed by Charles River Analytics, Inc. Please ask questions on answers.ros.org.

Kalman filter library

An efficient and robust multisensor-aided inertial navigation system with online calibration that is capable of fusing IMU, camera, LiDAR, GPS/GNSS, and wheel sensors. Use cases: VINS/VIO, GPS-INS, LINS/LIO, multi-sensor fusion for localization and mapping (SLAM). This repository also provides multi-sensor simulation and data.

ROS 2 localization for outdoor robots: IMU, wheel encoders and GPS fused in a 23-state UKF at 100 Hz. When the estimate goes wrong it reports which sensor and why, instead of drifting silently. Apache 2.0.

RTAB-Map library and standalone application

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.