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