EKF SLAM (Extended Kalman Filter SLAM)

Extended Kalman Filter SLAM (EKF SLAM) is a technique used by robots and autonomous vehicles to simultaneously map their environment and track their location within it. It combines measurements from sensors (like cameras or lasers) with a mathematical model of the robot's movements. EKF helps correct errors in these measurements by using probability, making the robot’s understanding of its position and surroundings more accurate over time. Essentially, it allows the robot to build a map while knowing where it is on that map, adapting as it gathers new information.