Performance of 6D LuM and FFS SLAM: an example for comparison using grid and pose based evaluation methods

Authors:
Rolf Lakaemper;Andreas Nüchter;Nagesh Adluru;Longin Jan Latecki
Affiliations:
Temple University, Philadelphia;University of Osnabrück, Germany;Temple University, Philadelphia;Temple University, Philadelphia
Venue:
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Year:
2007

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Abstract

The focus of this paper is on the performance comparison of two simultaneous localization and mapping (SLAM) algorithms namely 6D Lu/Milios SLAM and Force Field Simulation (FFS). The two algorithms are applied to a 2D data set. Although the algorithms generate overall visually comparable results, they show strengths & weaknesses in different regions of the generated global maps. The question we address in this paper is, if different ways of evaluating the performance of SLAM algorithms project different strengths and how can the evaluations be useful in selecting an algorithm. We will compare the performance of the algorithms in different ways, using grid and pose based quality measures.