A Deterministic Filter for Simultaneous Localization and Odometry Calibration of Differential-Drive Mobile Robots

Local reconstruction of differential-drive mobile robots position and orientation is made possible with an accurate odometry calibration. Starting from the encoders readings, and assuming an absolute measurement available, a deterministic filter to localize the vehicle while estimating a proper set of odometric parameters is proposed. A stability analysis guarantees that the position and orientation error decreases to zero and the estimation error of the odometric parameters is bounded. The proposed technique has been experimentally validated on a Khepera II mobile robot and compared to an Extended Kalman Filter approach. With both approaches the errors are practically the same, the proposed approach, thus, represents a computationally lighter alternative to Kalman approaches with a rigorous stability analysis.