EKF Sensor Fusion

This project implements the Extended Kalman Filter (EKF) to track the robot state (which is (x, y, yaw) in real time. The data from wheel encoder is used to predict the robot state in motion model. The measurement model utilizes the data from Apriltag landmark detection and the data from IMU sensor. The measurement of landmark is used to estimate the posterior from the prior generated by motion model. The measurement of yaw from IMU is used to further correctify the estimation of yaw.

Fuse odometry, imu and landmark detections:

Only fuse odometry and imu:

See more details about this project in my Github repo.