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, an 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 equations that remarkably reduce the systematic error of odometry. The new equations were derived to overcome the limitation of the conventional schemes. The second contribution is to propose the design guideline of the test track for calibration experiments. The calibration performance can be significantly improved by appropriate design of the test track. The numerical simulations and experimental results show that the odometry accuracy can be improved by the proposed calibration schemes.
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.
Odometry using incremental wheel encoder sensors provides the relative position of mobile robots. This relative position is fundamental information for pose estimation by various sensors for EKF Localization, Monte Carlo Localization etc. Odometry is also used as unique information for localization of environmental conditions when absolute measurement systems are not available. However, odometry suffers from the accumulation of kinematic modeling errors of the wheel as the robot's travel distance increases. Therefore, systematic odometry errors need to be calibrated. Principal systematic error sources are unequal wheel diameters and uncertainty of the effective wheelbase. The UMBmark method is a practical and useful calibration scheme for systematic odometry errors of two-wheel differential mobile robots. However, the approximation errors of the calibration equations and the coupled effect between the two systematic error sources affect the performance of the kinematic parameter estimation. In this paper, we proposed a new calibration scheme whose calibration equations have less approximation errors. This new scheme uses the orientation errors of the robot's final pose in the test track. This scheme also considers the coupled effect between wheel diameter error and wheelbase error. Numerical simulations and experimental results verified that the proposed scheme accurately estimated the kinematic error parameters and improved the accuracy of odometry calibration significantly.
Pose estimation for mobile robots depends basically on accurate odometry information. Odometry from the wheel's encoder is widely used for simple and inexpensive implementation. As the travel distance increases, odometry suffers from kinematic modeling errors regarding the wheels. Therefore, in order to improve the odometry accuracy, it is necessary that systematic errors be calibrated. The UMBmark test is a practical and useful scheme for calibrating the systematic errors of two-wheeled mobile robots. However, the square path track size used in the test has not been validated. A consideration of the calibration equations, experimental conditions, and modeling errors is essential to improve the calibration accuracy. In this paper, we analyze the effect on calibration performance of the approximation errors of calibration equations and nonsystematic errors under experimental conditions. Then, we propose a test track size for improving the accuracy of odometry calibration. From simulation and experimental results, we show that the proposed test track size significantly improves the calibration accuracy of odometry under a normal range of kinematic modeling errors for robots.
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