This paper describes a position estimation method of a wheeled mobile robot by integrating the informations in an odometric dead reckoning and a laser navigation system. The dead reckoning regularly gives the robot's position by the revolution counts of both side wheels. The laser navigation system succesively observes the bearing angles relative to the corner cube reflectors fixed in the robot's environment. The chi-squared hypothesis testing is applied to reliably identify the corner cubes. The identified angle measurements modify the robot's position calculated by the dead reckoning based on the Extended Kalman filtering. The plant model is introduced from the kinematic equation concerning the dead reckoning, which regards both the robot's position and the wheel's radius as the state variables and the encoder measurement as the input variable. The measurement model is built concerning the bearing to a corner cube reflector in environment observed by the scanned laser. The proposed method enables the robot to accurately estimate the position even under uncertainty of the wheel's radius and the robot's motion with slippage in the cluttered environment. The simulation and experimental results justify the proposed method.
