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Authors: Marco Rosano 1 ; Antonino Furnari 2 ; Luigi Gulino 3 and Giovanni Farinella 2

Affiliations: 1 Università degli Studi di Catania, Catania, Italy, OrangeDev s.r.l., via Vasco de Gama 91, Firenze, Italy ; 2 Università degli Studi di Catania, Catania, Italy ; 3 OrangeDev s.r.l., via Vasco de Gama 91, Firenze, Italy

ISBN: 978-989-758-402-2

ISSN: 2184-4321

Keyword(s): Visual Navigation, Reinforcement Learning, Image-based Localization, First Person Vision.

Abstract: Visual navigation algorithms allow a mobile agent to sense the environment and autonomously find its way to reach a target (e.g. an object in the environment). While many recent approaches tackled this task using reinforcement learning, which neglects any prior knowledge about the environments, more classic approaches strongly rely on self-localization and path planning. In this study, we compare the performance of single-target and multi-target visual navigation approaches based on the reinforcement learning paradigm, and simple baselines which rely on image-based localization. Experiments performed on discrete-state environments of different sizes, comprised of both real and virtual images, show that the two paradigms tend to achieve complementary results, hence suggesting that a combination of the two approaches to visual navigation may be beneficial.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Rosano, M.; Furnari, A.; Gulino, L. and Farinella, G. (2020). A Comparison of Visual Navigation Approaches based on Localization and Reinforcement Learning in Virtual and Real Environments. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-402-2; ISSN 2184-4321, pages 628-635. DOI: 10.5220/0008950806280635

@conference{visapp20,
author={Marco Rosano. and Antonino Furnari. and Luigi Gulino. and Giovanni Farinella.},
title={A Comparison of Visual Navigation Approaches based on Localization and Reinforcement Learning in Virtual and Real Environments},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2020},
pages={628-635},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008950806280635},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - A Comparison of Visual Navigation Approaches based on Localization and Reinforcement Learning in Virtual and Real Environments
SN - 978-989-758-402-2
IS - 2184-4321
AU - Rosano, M.
AU - Furnari, A.
AU - Gulino, L.
AU - Farinella, G.
PY - 2020
SP - 628
EP - 635
DO - 10.5220/0008950806280635

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