Research on Path Planning and Control of Driverless Logistics Train
Jinxiang Feng, Bo Yang, Xiaofei Pei, Pengwei Zhou · 2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) · 2021
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.