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Journal of Intelligent and Connected Vehicles 2022, 5(2): 88-98 https://doi.org/10.1108/JICV-01-2022-0003
Research paper | Open Access | Issue | Published: 11 April 2022

Longitudinal control for person-following robots

Show Author's Information Liang Wang1,  Jiaming Wu2,  Xiaopeng Li3( ),  Zhaohui Wu1,  Lin Zhu1
China Academy of Transportation Sciences, Beijing, China
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden
University of South Florida, Tampa, Florida, USA
Keywords:
Parameter optimization, Person following robot, Longitudinal control model
Cite this article:
Wang L, Wu J, Li X, et al. Longitudinal control for person-following robots. Journal of Intelligent and Connected Vehicles, 2022, 5(2): 88-98. https://doi.org/10.1108/JICV-01-2022-0003
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Abstract Full text About this article
Purpose

This paper aims to address the longitudinal control problem for person-following robots (PFRs) for the implementation of this technology.

Design/methodology/approach

Nine representative car-following models are analyzed from PFRs application and the linear model and optimal velocity model/full velocity difference model are qualified and selected in the PFR control.

Findings

A lab PFR with the bar-laser-perception device is developed and tested in the field, and the results indicate that the proposed models perform well in normal person-following scenarios.

Originality/value

This study fills a gap in the research on PRFs longitudinal control and provides a useful and practical reference on PFRs longitudinal control for the related research.


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Abstract
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About this article

Longitudinal control for person-following robots

Show Author's information Liang Wang1, Jiaming Wu2, Xiaopeng Li3( ), Zhaohui Wu1, Lin Zhu1
China Academy of Transportation Sciences, Beijing, China
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden
University of South Florida, Tampa, Florida, USA

Abstract

Purpose

This paper aims to address the longitudinal control problem for person-following robots (PFRs) for the implementation of this technology.

Design/methodology/approach

Nine representative car-following models are analyzed from PFRs application and the linear model and optimal velocity model/full velocity difference model are qualified and selected in the PFR control.

Findings

A lab PFR with the bar-laser-perception device is developed and tested in the field, and the results indicate that the proposed models perform well in normal person-following scenarios.

Originality/value

This study fills a gap in the research on PRFs longitudinal control and provides a useful and practical reference on PFRs longitudinal control for the related research.

Keywords: Parameter optimization, Person following robot, Longitudinal control model

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Publication history
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Publication history

Received: 25 January 2022
Revised: 27 February 2022
Accepted: 28 February 2022
Published: 11 April 2022
Issue date: May 2022

Copyright

© 2022 Liang Wang, Jiaming Wu, Xiaopeng Li, Zhaohui Wu and Lin Zhu. Published in Journal of Intelligent and Connected Vehicles. Published by Emerald Publishing Limited.

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This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode

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