Global Localization of Mobile Robots for Indoor Environments Using Natural Landmarks

Abstract

This paper introduces a global localization system based on natural landmarks for indoor mobile robots. The proposed approach is based on recognition of natural landmarks from laser scanner data. A previously built grid-based map is pre-processed off-line to obtain a model of landmarks and their attributes for each cell. The robot's position and orientation are calculated by finding correspondence between the identified landmarks from robot's current position and the landmarks associated to the model. This proposed approach called GL2 follows a two stage process. Initially a fast initial filter based on the number and type of landmarks is used to substantially reduce the search space. The second stage uses a modified discrete relaxation algorithm to perform a more detailed analysis and find the robot's location and orientation. It is shown the robustness of the algorithm in complex and real office like environments, even in the presence of previously unknown obstacles