Visual map matching and localization using a global feature map
- 1 June 2008
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
This paper presents a novel method to support environmental perception of mobile robots by the use of a global feature map. While typical approaches to simultaneous localization and mapping (SLAM) mainly rely on an on-board camera for mapping, our approach uses geographically referenced aerial or satellite images to build a map in advance. The current position on the map is determined by matching features from the on-board camera to the global feature map. The problem of feature matching is posed as a standard point pattern matching problem and a solution using the iterative closest point method is given. The proposed algorithm is designed for use in a street vehicle and uses lane markings as features, but can be adapted to almost any other type of feature that is visible in aerial images. Our approach allows for estimating the robot position at a higher precision than by a purely GPS-based localization, while at the same time providing information about the environment far beyond the current field of view.Keywords
This publication has 16 references indexed in Scilit:
- Robust vehicle localization in urban environments using probabilistic mapsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- A Study of the Rao-Blackwellised Particle Filter for Efficient and Accurate Vision-Based SLAMInternational Journal of Computer Vision, 2007
- Monocular SLAM for Visual OdometryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- Realtime lane tracking of curved local roadPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Unscented SLAM for large-scale outdoor environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Visual odometryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- A fast expected time algorithm for the 2-D point pattern matching problemPattern Recognition, 2004
- Die Radontransformation in der digitalen Bildverarbeitung (The Radon Transform in Digital Image Processing)at – Automatisierungstechnik, 2002
- Iterative point matching for registration of free-form curves and surfacesInternational Journal of Computer Vision, 1994
- A method for registration of 3-D shapesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1992