Abstract

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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