Range sensing, localization, and error elimination of two-wheeled mobile robots

In this paper, the platform of a two-wheeled mobile robot (TWMR) is studied and the bias errors about postures of TWMR, i.e., effects of skidding and slipping, are classified and modeling. The data of range sensors are processed as localization methods to eliminate the external error which encoder odometry cannot be detected. Two concepts about localization method fusion and error elimination architecture are proposed. The first one combines results of localization methods and determines the best results based on the performance of localization methods in different scenarios. The second one contains the former and makes the posture information more reliable. In addition, the methods could correct the encoder odometry with the knowledge of skidding and slipping.