Abstract: Localization and map building are two essential tasks for an autonomous mobile robot0s indoor navigation without a priori map. This paper provides a method for mobile robot indoor simultaneous localization and mapping using laser range finder and monocular vision. Due to variant sensor modeling for laser range finder and CCD camera, weighted least square fitting and non-local maximum suppression algorithm are used to extract certain 2-D horizontal environmental features and vertical edges respectively. We also present an approach to complete EKF localization and metric map building simultaneously based on the result of lines merging and feature fusion. Experiment results with the SmartROB-2 mobile robot and data analysis show the method0s validity and practi cability.