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Evaluating Multi-Agent Robotic Systems Using Ground Truth (bibtex) [pdf]
@InProceedings{stulp04evaluating,
author =       {Freek Stulp and Suat Gedikli and Michael Beetz},
title =        {Evaluating Multi-Agent Robotic Systems Using Ground Truth},
year =         {2004},
booktitle =    {Proceedings of the Workshop on Methods and Technology for Empirical Evaluation of Multi-agent Systems and Multi-robot Teams (MTEE)},
bib2html_pubtype  = {Refereed Conference Paper},
bib2html_rescat   = {Perception, Models},
bib2html_groups   = {AGILO},
bib2html_funding  = {AGILO},
bib2html_keywords = {},
abstract          = {A thorough empirical evaluation of multi-agent robotic
systems is greatly facilitated if the {\em true} state of the world over time
can be obtained. The accuracy of the beliefs as well as the overall
performance can then be measured objectively and efficiently. In this paper we
present a system for determining the {\em ground truth} state of the world,
similar to the ceiling cameras used in RoboCup small-size league. We have used
this ground truth data to evaluate the accuracy of the self- and
object-localization of the robots in our RoboCup mid-size league team, the
Agilo RoboCuppers. More complex models of the state estimation module have
also been learned. These models provide insight into the workings and
shortcomings of this module, and can be used to improve it.}
}