A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots

  • Authors:
  • Sebastian Thrun;Wolfram Burgard;Dieter Fox

  • Affiliations:
  • Computer Science Department and Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213-3891, http://www.cs.cmu.edu/∼thrun;Institut für Informatik III, Universität Bonn, D-53117 Bonn, Germany, http://www.cs.uni-bonn.de/∼wolfram, http://www.cs.uni-bonn.de/∼fox;Institut für Informatik III, Universität Bonn, D-53117 Bonn, Germany, http://www.cs.uni-bonn.de/∼wolfram, http://www.cs.uni-bonn.de/∼fox

  • Venue:
  • Autonomous Robots
  • Year:
  • 1998

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper addresses the problem of building large-scalegeometric maps of indoor environments with mobile robots. It posesthe map building problem as a constrained, probabilisticmaximum-likelihood estimation problem. It then devises a practicalalgorithm for generating the most likely map from data, along with themost likely path taken by the robot. Experimental results in cyclicenvironments of size up to 80×25 m illustrate theappropriateness of the approach.