Simultaneous Localization and Mapping for Robot under Colored Measurement Noise

Abstract

Aiming at colored measurement noise model,this paper presents a Simultaneous Localization and Mapping(SLAM) algorithm for wheeled robot under colored measurement noise.Colored measurement noise model is converted into white measurement noise model by recombining the process model and the measurement model for wheeled robot.In order to make the process noise and the measurement noise irrelevant each other,the process model is re-defined.Estimating state and mapping are conducted in accordance with the virtual process model and the virtual measurement model.In data association step,part observed landmarks are processed as redundant landmarks.Some indicators of the filter are used to evaluate the performance the algorithm.Simulation results show that the algorithm is consistent and robust.