Quality Evaluation of the Occupancy Grids without Ground Truth Maps

Ilze Andersone

Abstract

Robot map merging is an important task in mobile multi-robot systems to facilitate cooperation and higher performance. Map merging has been extensively researched in recent years, but little attention has been paid to the merging of maps that have different quality levels. In this paper a method is proposed that allows the quality evaluation of occupancy grid maps without the need for ground truth maps. The method uses Convolutional Neural Network (CNN) for map fragment classification and can be used for overall map quality evaluation as well as for evaluation of map regions, which is especially useful for map merging purposes.

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Paper Citation


in Harvard Style

Andersone I. (2020). Quality Evaluation of the Occupancy Grids without Ground Truth Maps.In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-395-7, pages 319-326. DOI: 10.5220/0009175503190326


in Bibtex Style

@conference{icaart20,
author={Ilze Andersone},
title={Quality Evaluation of the Occupancy Grids without Ground Truth Maps},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2020},
pages={319-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009175503190326},
isbn={978-989-758-395-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Quality Evaluation of the Occupancy Grids without Ground Truth Maps
SN - 978-989-758-395-7
AU - Andersone I.
PY - 2020
SP - 319
EP - 326
DO - 10.5220/0009175503190326