A comparison of SLAM algorithms based on a graph of relations

Authors:
Wolfram Burgard;Cyrill Stachniss;Giorgio Grisetti;Bastian Steder;Rainer Kümmerle;Christian Dornhege;Michael Ruhnke;Alexander Kleiner;Juan D. Tardós
Affiliations:
University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany;University of Freiburg, Dept. of Computer Science, Freiburg, Germany and Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza, Zaragoza, Spain
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

In this paper, we address the problem of creating an objective benchmark for comparing SLAM approaches. We propose a framework for analyzing the results of SLAM approaches based on a metric for measuring the error of the corrected trajectory. The metric uses only relative relations between poses and does not rely on a global reference frame. The idea is related to graph-based SLAM approaches in the sense that it considers the energy needed to deform the trajectory estimated by a SLAM approach to the ground truth trajectory. Our method enables us to compare SLAM approaches that use different estimation techniques or different sensor modalities since all computations are made based on the corrected trajectory of the robot. We provide sets of relative relations needed to compute our metric for an extensive set of datasets frequently used in the SLAM community. The relations have been obtained by manually matching laser-range observations. We believe that our benchmarking framework allows the user an easy analysis and objective comparisons between different SLAM approaches.