ekf-localization

An open source platform for visual-inertial navigation research.

IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP

An in-depth step-by-step tutorial for implementing sensor fusion with robot_localization! 🛰

Fusing GPS, IMU and Encoder sensors for accurate state estimation.

Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion. ICCA 2018

State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).

A monocular plane-aided visual-inertial odometry

using hloc for loop closure in OpenVINS

Self-position estimation by eskf by measuring gnss and imu

Interface for OpenVINS with the maplab project

Sensor fusion between IMU, GNSS and Lidar data using an Error State Extended Kalman Filter.

Introducing various sensors to our Gazebo Harmonic simulation

C++ Library for INS-GPS Extended-Kalman-Filter (Error State Version)

Secondary posegraph adapted for interfacing with OpenVINS, based on VINS-Mono / VINS-Fusion.

An extended Kalman Filter implementation in Python for fusing lidar and radar sensor measurements

EKF-based LiDAR-Inertial Map matching Localization

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

A Master of Engineering Academic Project

This code is associated with the paper submitted to Encyclopedia of EEE titled: Robot localization: An Introduction