An open source platform for visual-inertial navigation research.

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.

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

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

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).

Interface for OpenVINS with the maplab project

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

This project builds a ROS-based Autonomous Robot from scratch

Master Thesis on processing point clouds from Velodyne VLP-16 LiDAR sensors with PCL in ROS to improve localization method, based on Extended Kalman Filter.

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

C++ Code to study Kalman, Extended Kalman Filters, and Monte Carlo localization algorithm

ROS Turtlebot with Extended Kalman Filters

Localization with EKF algorithm

This project is an implementation of a Sensor Fusion Module between LIDAR and RADAD sensors for tracking an object; using the Extended Kalman Filter Algorithm.

双标签定位

Extended Kalman Filter Localization Lab using ROS

My bachelor's thesis (ГУАП 2017. Ковалев А. Д. Группа 3321) as of May, 2017. New stuff is here: https://github.com/ToastyToast/slam-algorithms

React.js App for autonomous robot using Extended Kalman FIlter (EKF) and PID controller.

IIT(BHU)

This is sample codes for robotics algorithms.

SLAM Course by Cyrill Stachniss, University of Freiburg. Winter 2013. Assigments