Simultaneous Localization and Mapping with Stereovision

Abstract

This paper presents a simultaneous localization and mapping approach based on an extended kalman filter, using only a set of non-registered stereovision image pairs. Invariant image point features are used to detect 3D landmarks and to provide local motion estimates. The 3D coordinates of each point feature are computed by stereovision, and an interest point matching algorithm solves the data association problem. The estimation of the errors on the local motion estimations, on the landmark initialisations and on the landmark observations are depicted, and results with low altitude aerial images are presented.