Position tracking of house robot based on laserfinder

An algorithm for Extended Kalman Filter (EKF) based on Simultaneous Localization and Map building is presented by establishing House Robots kinematics model with conventional off-centered orientable wheel and integrating scans from a time-of-flight laser and odometer readings from a mobile robot. The algorithm continued track position using a laser scanner and artificial landmarks, matching the sensor data to the features was straightforward, and outliers could be filtered out effectively by validation gates. Simulation results show that the method performs position tracking very well in an indoor environment.