Odometry using wheel encoders provides fundamental pose estimates for wheeled mobile robots. Systematic errors of odometry can be reduced by the calibration of kinematic parameters. The UMBmark method is one of the widely used calibration schemes for two wheel differential mobile robot. In this paper, the accurate calibration scheme of kinematic parameters is proposed by extending the conventional UMBmark. The contributions of this paper can be summarized as two issues. The first contribution is to present new calibration scheme that reduce the approximation error of calibration equations in UMBmark method. The new equations were derived from the robot's final orientation errors in test track. The second contribution is to propose the consideration of the coupled effects between wheel diameter errors and wheelbase errors in test track for calibration experiments. The calibration performance can be significantly improved by applying new calibration equations were derived to overcome the limitations of the conventional scheme. The numerical simulations and experimental results show that the odometry accuracy can be improved by the proposed calibration schemes.

For outdoor navigation, it is necessary to find the relevant features of outdoor road environments and detect drivable region for robot's motion. This paper presents a methodology for extracting the drivable road region by detecting the prominent road features and obstacles through a single laser range finder. The prominent features of roads are curbs and the road surface. The laser range finder is mounted on the mobile robot, looks down the road with a small tilt angle, and obtains two-dimensional range data. The proposed method is computationally more efficient in comparison with vision-based techniques and applicable for various road conditions in target environment. Experimental results confirm the reliability of the algorithm.