Correction robot pose for SLAM based on extended Kalman filter in a rough surface environment

Abstract

This research deals with mobile robot SLAM algorithm based on extended Kalman filter. To enhance a accuracy of robot pose, one more extended Kalman filter is used in a rough surface environment. The robot has uncertain kinematic model due to a caterpillar. When the robot drives on irregular surface, it's heading can be corrupted. We propose a method to correct uncertain robot pose using one more extended Kalman filter through simulation results.