Longitudinal control for person-following robots

Liang Wang;Jiaming Wu;Xiaopeng Li;Zhaohui Wu;Lin Zhu
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引用次数: 3

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.
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人跟机器人的纵向控制
目的-本文旨在解决人跟机器人(PFR)的纵向控制问题,以实现该技术。设计/方法/方法-从PFR应用中分析了九个具有代表性的跟车模型,并在PFR控制中确定和选择了线性模型和最优速度模型/全速差模型。研究结果-开发了一种带有条形激光感知设备的实验室PFR,并在现场进行了测试,结果表明,所提出的模型在正常人跟随场景中表现良好。原创性/价值-本研究填补了PRFs纵向控制研究的空白,为相关研究提供了有益和实用的PFRs纵向控制参考。
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Front Cover Contents Advancements and Prospects in Multisensor Fusion for Autonomous Driving Extracting Networkwide Road Segment Location, Direction, and Turning Movement Rules From Global Positioning System Vehicle Trajectory Data for Macrosimulation Decision Making and Control of Autonomous Vehicles Under the Condition of Front Vehicle Sideslip
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