BEARING-ONLY SAM USING A MINIMAL INVERSE DEPTH PARAMETRIZATION - Application to Omnidirectional SLAM

Abstract

INRIA Sophia Antipolis M´editerran´ee, 2004 route des Lucioles, Sophia Antipolis Cedex, Francecyril.joly@sophia.inria.fr, patrick.rives@sophia.inria.frKeywords: Simultaneous Localization and Mapping (SLAM), Smoothing and Mapping (SAM), ExtendedKalman Filter (EKF), Bearing-Only, Inverse Depth RepresentationAbstract: Safe and efficient navigation in large-scale unknown environments remains a key problem whichhas to be solved to improve the autonomy of mobile robots. SLAM methods can bring the mapof the world and the trajectory of the robot. Monucular SLAM is a difficult problem. Currently,it is solved with an Extended Kalman Filter (EKF) using the inverse depth parametrization.However, it is now well known that the EKF-SLAM become inconsistent when dealing with largescale environments. Moreover, the classical inverse depth parametrization is over-parametrized,which can also be a cause of inconsistency. In this paper, we propose to adapt the inverse depthrepresentation to the more robust context of smoothing and mapping (SAM). We show that ouralgorithm is not over-parametrized and that it gives very precise results on real data.