The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

Filters: KF, EKF, UKF || Process Models: CV, CTRV || Measurement Models: Radar, Lidar

State estimation, smoothing and parameter estimation using Kalman and particle filters.

A compact Extended Kalman Filter (EKF) library for real time embedded system (with template for Teensy4/Arduino and STM32CubeIDE)

State estimation and filtering algorithms in Go

This is an open source Kalman filter C++ library based on Eigen3 library for matrix operations. The library has generic template based classes for most of Kalman filter variants including: (1) Kalman Filter, (2) Extended Kalman Filter, (3) Unscented Kalman Filter, and (4) Square-root UKF..

Self-position estimation by eskf by measuring gnss and imu

A novel architecture in which the Factor Graph Optimization (FGO) is hybrid with the Extended Kalman Filter (EKF) for tightly coupled GNSS/UWB integration with online Temporal calibration (FE-GUT).

Kalman filter sanctuary - including continuous-discrete extended Kalman filter. Bring additional filters here for a bigger collection.

Neural-Kalman GNSS/INS Navigation for Precision Agriculture

3D-PointMass-EKF for State Estimation coupled with STM-UKF for Side Slip Angle Estimation

3D Pose Estimation of the Planar Robot Using Extended Kalman Filter

Maximum Correntropy Kalman Filter

A C++ implementation of the Kalman filter and its extension, the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) using Eigen.

Unscented Kalman Filter in C code and MATLAB code - Easy to use

Modified Extended Kalman Filter with generalized exponential Moving Average and dynamic Multi-Epoch update strategy (MEKF_MAME)

AutonomousRobots Series

This repository consists the entire solution code for the course SLAM - by Claus Brenner. All solutions have been written in Python 3. You can find the video tutorials on YouTube.

Sensor Fusion of GPS and IMU with Extended Kalman Filter for Localization in Autonomous Driving

This is a relatively low level implementation of a kalman filter; with support for extended and iterative extended kalman filters. The goals of the project are to provide a numerically stable, robust EKF implementation which is both fast and portable.