Fusing Lidar and Radar data with Extended Kalman Filter (EKF)

EKF_SLAM Implementation using LIDAR, GPS and Odometer measurement

A driving dataset for the development and validation of fused pose estimators and mapping algorithms

This is a simple matlab implementation of a 2D tracking with Extended Kalman Filter

Project for Introduction to Sensing and Estimation in Robotics

Extented Kalman Filter for 6D pose estimation using gps, imu, magnetometer and sonar sensor.

基于间接卡尔曼滤波的IMU与GPS融合MATLAB仿真（IMU与GPS数据由仿真生成）

EKF IMU Fusion Algorithms

EKF-SLAM TOOLBOX FOR MATLAB

A Simultaneous Localisation and Mapping simulation in MATLAB

I_UWB_LPS-MatlabProject

An Extended Kalman Filter (that uses a constant velocity model) in C++. This EKF fuses LIDAR and RADAR sensor readings to estimate location (x,y) and velocity (vx, vy).

Sensor fusion algorithm for UWB, IMU, GPS locating data.

UAV positioning with UWB and IMU

An application for Data Collection of Video Sequences using the Flea3 USB3 Camera; GPS and IMU (UTC IMU02) readings are framestamped in separate files.

This library provides a basic, EKF based, implementation for a pose estimator that is able to fuse IMU, odometry and global positioning information (GPS)

This is a repo for my master thesis research about the Fusion of Visual SLAM and GPS. It contains the research paper, code and other interesting data.

GPS calibration using points cloud slam and other sensors