基于双变量限幅PID算法的四轮差速转向AGV导航控制系统  

Four-wheel differential steering AGV navigation control system based on double variable limiters PID algorithm

作　　者：刘梓博 陈羽立 徐梓峰 李鑫 周志艳[1,2,3,4,5,6] LIU Zibo;CHEN Yuli;XU Zifeng;LI Xin;ZHOU Zhiyan(College of Engineering,South China Agricultural University and Guangdong Laboratory for Lingnan Modern Agriculture,Guangzhou 510642,China;Guangdong Provincial Key Laboratory of Agricultural Artificial Intelligence(GDKL-AAI),Guangzhou 510642,China;Guangdong Engineering Research Center for Agricultural Aviation Application(ERCAAA),Guangzhou 510642,China;Key Laboratory of Key Technology on Agricultural Machine and Equipment(South China Agricultural University),Ministry of Education,Guangzhou 510642,China;State Key Laboratory of Agricultural Equipment Technology,Guangzhou 510642,China;Key Technology Innovation Research Center of Rice Smart Farming of South China Agricultural University-Dongyuan County,Heyuan 517554,China)

机构地区：[1]华南农业大学工程学院/岭南现代农业科学与技术广东省实验室,广州510642 [2]广东省农业人工智能重点实验室,广州510642 [3]广东省农业航空应用工程技术研究中心,广州510642 [4]华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642 [5]农业装备技术全国重点实验室,广州510642 [6]华南农业大学-东源县水稻智慧农场关键技术创新研究中心,河源517554

出　　处：《农业工程学报》2025年第5期27-37,共11页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家重点研发计划项目(2022YFD2001501);井冈山农高区省级科技专项“揭榜挂帅”项目(20222-051252-02);广东省科技计划项目(2023B10564002)。

摘　　要：四轮差速转向AGV(automated guided vehicle,自动导引车)具有灵活性好、转弯半径小、机械结构复杂度低等特点,在丘陵山地农业生产中更有优势。针对传统阿克曼底盘导航算法直接应用于差速转向底盘导航所存在转弯半径过大、易导致导航失效的问题,该研究使用模块化分层开发思想,基于ROS(robot operating system,机器人操作系统)设计了一种基于双变量限幅PID的差速转向底盘导航控制算法,并通过改造的四轮差速车辆进行试验。算法通过横向偏差与航向角偏差双变量限幅PID得到前进速度与旋转角速度,再通过下位单片机实现车轮转速的闭环控制。通过仿真试验,水泥路面试验和田间试验,以横向偏差平均值、均方根误差与最大偏差3个方面对算法的准确性与适应能力进行验证。仿真试验结果表明:通过路径跟踪算法控制的四轮差速车辆在0.4 m/s的速度行驶时,平均误差为1.15 cm,均方根误差为1.27 cm,上线距离小于4.09 m,导航系统有较好的稳定性和调节能力。在水泥地试验中水泥路面环境下以0.4 m/s速度行驶时,平均误差2.83 cm,均方根误差为3.21 cm,在田间试验的果树行间路面环境下以0.4 m/s速度行驶时,平均误差5.25 cm,均方根误差6.13 cm。田间试验结果表明,导航系统与试验车辆在不同的地形环境下有着较好的适应能力,研究结果可以为差速转向底盘的导航技术提供参考。The current algorithm of differential vehicle navigation cannot fully meet the optimal turning radius,long-distance path tracking,and simple navigation logic.In this study,a navigation control algorithm was proposed using ROS(robot operating system),according to modular and hierarchical development.The four-wheel differential speed vehicle was also transformed for testing.The target path was described by the target point plus the target yaw angle.The target path was an infinite straight line through the target point,whose direction was the target yaw angle.The vehicle started from any position,then approached the target path,and finally reached the target point.The kinematic equation of the vehicle was obtained by the kinematic analysis of the four-wheel differential speed vehicle.There was a relationship between the forward speed and steering speed of the vehicle,with the speed of the left and right wheels.Then the coordinate transformation was implemented to obtain the lateral deviation between the vehicle and the target path,and the longitudinal distance between the target point and the vehicle.The required forward speed was calculated using the longitudinal distance.The driving angle close to the target path was determined using the lateral deviation.Then the required steering speed was obtained after the difference between the driving angle and the yaw angle of the vehicle.Two advantages were gained during optimization.One was to improve the robustness and flexibility of the algorithm,which was stably solved under any size of lateral deviation and simplified the complexity of path planning.The algorithm was freely switched to the target path of the task,whether to focus or ignore the path planning among lines.Another was that the internal parameters of the algorithm all shared specific meanings,which were easy to understand and adjust,according to different needs under the different environments and operations.The above calculation was realized by the double variable limiter PID algorithm.The forward speed a

关 键 词：底盘 PID 差速转向 ROS 路径跟踪 双变量限幅 

分 类 号：S147.2[农业科学—肥料学]