Feature Selection Criteria for EKF-SLAM Algorithm Correction Stage

FERNANDO AUAT CHEEIN; GUSTAVO SCAGLIA; RICARDO CARELLI

Congreso; Reunión de Trabajo en Procesamiento de la Información y Control (RPIC2009); 2009

This paper presents an environmental feature selection procedure for the correction stage of a SLAM (Simultaneous Localization and Mapping) algorithm based on an Extended Kalman Filter (EKF). This approach decreases the computational time needed for the correction stage allowing real and constant time implementations of the SLAM. The entire system is implemented on a mobile robot with a range laser sensor incorporated on it. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing- time consumed by the corrected SLAM are also shown in this work.