Navigation of an autonomous mobile robot using data association method

This paper presents an investigation on the performance of Unscented HybridSLAM using two different mapping strategies. The global map estimation using Unscented Kalman Filter is scrutinized for different scenarios, with and without the influence of a data association process. The accuracy of generated global map under different vehicle speed settings and with different process time is demonstrated using computer simulation. Results are discussed in terms of Root Mean Square (RMS) position error, orientation error, and time of navigation process. Results show that depending on the application, and on a desired speed, a compromise has to be done to get the best efficacy.