Longitudinal control for person-following robots
Artikel i vetenskaplig tidskrift, 2022

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.

Parameter optimization

Longitudinal control model

Person following robot


Liang Wang

China Academy of Transportation Sciences

Jiaming Wu


Xiaopeng Li

University of South Florida

Zhaohui Wu

China Academy of Transportation Sciences

Lin Zhu

China Academy of Transportation Sciences

Journal of Intelligent and Connected Vehicles

23999802 (eISSN)

Vol. 5 2 88-98


Robotteknik och automation




Mer information

Senast uppdaterat