A Probabilistic Approach for Concurrent Map Acquisition and Localization for Mobile Robots

Abstract

This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from data, along with the most likely path taken by the robot. Experimental results in cyclic environments of size up to 80 by 25 meter illustrate the appropriateness of the approach. y These authors are affiliated with the Institut fur Informatik III, Universat Bonn, Germany The research was financially supported by Daimler Benz Research, Germany. Keywords: autonomous robots, Baum-Welch, mobile robots, navigation, localization, mapping, positioning, probabilistic algorithms, robot mapping A Probabilistic Approach for Concurrent Map Acquisition and Localization 1 1 Introduction Over the last two decades or so, the problem of acquiring maps in large-scale indoor environments has received con...