An Evaluation between Global Appearance Descriptors based on Analytic Methods and Deep Learning Techniques for Localization in Autonomous Mobile Robots

Sergio Cebollada, Luis Payá, David Valiente, Xiaoyi Jiang, Oscar Reinoso

Abstract

In this work, different global appearance descriptors are evaluated to carry out the localization task, which is a crucial skill for autonomous mobile robots. The unique information source used to solve this issue is an omnidirectional camera. Afterwards, the images captured are processed to obtain global appearance descriptors. The position of the robots is estimated by comparing the descriptors contained in the visual model and the descriptor calculated for the test image. The descriptors evaluated are based on (1) analytic methods (HOG and gist) and (2) deep learning techniques (auto-encoders and Convolutional Neural Networks). The localization is tested with a panoramic dataset which provides indoor environments under real operating conditions. The results show that deep learning based descriptors can be also an interesting solution to carry out visual localization tasks.

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Paper Citation


in Harvard Style

Cebollada S., Payá L., Valiente D., Jiang X. and Reinoso O. (2019). An Evaluation between Global Appearance Descriptors based on Analytic Methods and Deep Learning Techniques for Localization in Autonomous Mobile Robots.In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-380-3, pages 284-291. DOI: 10.5220/0007837102840291


in Bibtex Style

@conference{icinco19,
author={Sergio Cebollada and Luis Payá and David Valiente and Xiaoyi Jiang and Oscar Reinoso},
title={An Evaluation between Global Appearance Descriptors based on Analytic Methods and Deep Learning Techniques for Localization in Autonomous Mobile Robots},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2019},
pages={284-291},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007837102840291},
isbn={978-989-758-380-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - An Evaluation between Global Appearance Descriptors based on Analytic Methods and Deep Learning Techniques for Localization in Autonomous Mobile Robots
SN - 978-989-758-380-3
AU - Cebollada S.
AU - Payá L.
AU - Valiente D.
AU - Jiang X.
AU - Reinoso O.
PY - 2019
SP - 284
EP - 291
DO - 10.5220/0007837102840291