{"title":"Research on Path Planning and Control of Driverless Logistics Train","authors":"Jinxiang Feng, Bo Yang, Xiaofei Pei, Pengwei Zhou","doi":"10.1109/CVCI54083.2021.9661132","DOIUrl":null,"url":null,"abstract":"Driverless logistics train is an important application of driverless vehicle in the field of cargo transportation. In this paper, firstly, the kinematics modeling of the driverless logistics train platform is carried out, and its kinematics characteristics are analyzed. Then, based on the driverless logistics train platform, a path planning algorithm based on quintic polynomial and a path tracking control strategy based on feedforward and feedback are proposed. The control method of linear quadratic regulator (LQR) is adopted in the feedback control, and its goal is to reduce the lateral error and direction deviation between the vehicle and the target path. Finally, vehicle experiments are carried out based on the driverless logistics train, and the results verify the effectiveness and accuracy of the proposed method. In addition, in the experiment on the campus road, considering the inaccurate positioning and drift of GPS in the shade of trees, the positioning method of Simultaneous Localization and Mapping (SLAM) is used, which can solve the above problems effectively.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI54083.2021.9661132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Driverless logistics train is an important application of driverless vehicle in the field of cargo transportation. In this paper, firstly, the kinematics modeling of the driverless logistics train platform is carried out, and its kinematics characteristics are analyzed. Then, based on the driverless logistics train platform, a path planning algorithm based on quintic polynomial and a path tracking control strategy based on feedforward and feedback are proposed. The control method of linear quadratic regulator (LQR) is adopted in the feedback control, and its goal is to reduce the lateral error and direction deviation between the vehicle and the target path. Finally, vehicle experiments are carried out based on the driverless logistics train, and the results verify the effectiveness and accuracy of the proposed method. In addition, in the experiment on the campus road, considering the inaccurate positioning and drift of GPS in the shade of trees, the positioning method of Simultaneous Localization and Mapping (SLAM) is used, which can solve the above problems effectively.
无人驾驶物流列车是无人驾驶车辆在货物运输领域的重要应用。本文首先对无人驾驶物流列车平台进行运动学建模,并对其运动学特性进行分析。然后,基于无人驾驶物流列车平台,提出了一种基于五次多项式的路径规划算法和基于前馈和反馈的路径跟踪控制策略。在反馈控制中采用线性二次型调节器(LQR)的控制方法,其目标是减小车辆与目标路径之间的横向误差和方向偏差。最后,基于无人驾驶物流列车进行了车辆实验,结果验证了所提方法的有效性和准确性。此外,在校园道路实验中,考虑到GPS在树荫下定位不准确、漂移等问题,采用了同时定位与测绘(Simultaneous Localization and Mapping, SLAM)的定位方法,有效解决了上述问题。