Home /Research /Longitudinal control for person-following robots
PERCEPTION

Longitudinal control for person-following robots

Liang Wang, Jiaming Wu, Xiaopeng Li, Zhaohui Wu, Lin Zhu

Year
2022
Citations
10
Access
Open access

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

Longitudinal studyOriginalityControl (management)Field (mathematics)Computer scienceLongitudinal fieldRobotPerceptionLongitudinal dataSimulation

Related papers

Browse all PERCEPTION papers