Intention Indication for Human Aware Robot Navigation

Oskar Palinko, Eduardo R. Ramirez, Norbert Krüger, William K. Juel, Leon Bodenhagen

2020

Abstract

Robots are gradually making their ways from factory floors to our everyday living environments. Mobile robots are becoming more ubiquitous in many domains: logistics, entertainment, security, healthcare, etc. For robots to enter the everyday human environment they need to understand us and make themselves understood. In other words, they need to make their intentions clear to people. This is especially important regarding intentions of movement: when robots are starting, stopping, turning left, right, etc. In this study we explore three different ways for a wheeled mobile robot to communicate its intentions on which way it will go at a hallway intersection: one analogous to automotive signaling, another based on movement gesture and as a third option a novel light signal. We recorded videos of the robot approaching an intersection with the given methods and asked subjects via a survey to predict the robot’s actions. The car analogy and turn gesture performed adequately, while the novel light signal less so. In the following we describe the setup and outcomes of this study, as well as give suggestions on how mobile robots should signal in indoor spaces based on our findings.

Paper Citation

in Harvard Style

Palinko O., Ramirez E., Juel W., Krüger N. and Bodenhagen L. (2020). Intention Indication for Human Aware Robot Navigation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 2: HUCAPP; ISBN 978-989-758-402-2, SciTePress, pages 64-74. DOI: 10.5220/0009167900640074

in Bibtex Style

@conference{hucapp20,
author={Oskar Palinko and Eduardo R. Ramirez and William K. Juel and Norbert Krüger and Leon Bodenhagen},
title={Intention Indication for Human Aware Robot Navigation},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 2: HUCAPP},
year={2020},
pages={64-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009167900640074},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 2: HUCAPP
TI - Intention Indication for Human Aware Robot Navigation
SN - 978-989-758-402-2
AU - Palinko O.
AU - Ramirez E.
AU - Juel W.
AU - Krüger N.
AU - Bodenhagen L.
PY - 2020
SP - 64
EP - 74
DO - 10.5220/0009167900640074
PB - SciTePress