基于动态前视距离纯追踪模型的温室农机路径跟踪研究*

doi:10.13733/j.jcam.issn.20955553.2021.11.10

中国农机化学报 ›› 2021, Vol. 42 ›› Issue (11): 58-64.DOI: 10.13733/j.jcam.issn.20955553.2021.11.10

• 设施农业与植保机械工程 • 上一篇下一篇

基于动态前视距离纯追踪模型的温室农机路径跟踪研究^*

柴善鹏¹, 姚立健¹, 徐丽君², 陈钦汉¹, 徐涛涛¹, 杨岩坤¹

1.浙江农林大学光机电工程学院,杭州市,311300;
2.浙江农林大学集贤学院,杭州市,311300

收稿日期:2021-06-24 修回日期:2021-08-27 出版日期:2021-11-15 发布日期:2021-11-15
通讯作者: 姚立健,男,1974年生,江苏建湖人,博士,教授,博导;研究方向为智能农业装备与农业机器人等。E-mail: ljyao@zafu.edu.cn
作者简介:柴善鹏,男,1997年生,浙江瑞安人,硕士研究生;研究方向为农业机器人导航控制。E-mail: 1074110017@qq.com
基金资助:
*浙江省基础公益研究计划项目(LGN18F030001)

Research on greenhouse agricultural machinery path tracking based on dynamic look ahead distance pure pursuit model

Chai Shanpeng¹, Yao Lijian¹, Xu Lijun², Chen Qinhan¹, Xu Taotao¹, Yang Yankun¹

1. College of Optical, Mechanical and Electrical Engineering, Zhejiang A & F University, Hangzhou, 311300, China;
2. College of JiXian Honors, Zhejiang A & F University, Hangzhou, 311300, China

Received:2021-06-24 Revised:2021-08-27 Online:2021-11-15 Published:2021-11-15

摘要/Abstract

摘要： 为提高温室内智能农机自动导航的路径跟踪精度,提出一种基于粒子群算法的纯追踪模型动态前视距离确定方法及其路径跟踪控制方法。利用超宽带(UWB)模块和电子陀螺获取温室内智能农机的位置偏差和航向偏差;为提高纯追踪模型的自适应能力,对农机位姿偏差进行定量分析并根据位姿偏差程度构建适应度函数,通过粒子群优化(PSO)算法实时确定纯追踪模型中的最优前视距离,为提升算法求解效率对惯性权重系数进行改进;根据农机位姿偏差程度构建速度控制函数对农机进行变速控制。样机试验结果表明:在3种初始状态下的直线路径跟踪时,平均偏差均值为24.4 cm,稳态偏差平均值为4.3 cm,导航时间平均值为13.2 s,稳定距离平均值为318.1 cm。路径跟踪的各项指标均优于同等条件下的恒速固定视距试验。

关键词: 农业机械, 粒子群算法, 纯追踪, 动态前视距离, 路径跟踪

Abstract: In order to improve the path tracking accuracy of intelligent agricultural machinery automatic navigation in the greenhouse, a distance determination method based on dynamic look ahead distance pure pursuit model and its path tracking control method was proposed. The position deviation and heading deviation of the intelligent agricultural machinery in the greenhouse are obtained using the Ultra Wide Band (UWB) module and the electronic gyroscope. In order to improve the adaptive ability of the pure pursuit model, a quantitative analysis of the posture deviation of the agricultural machinery and the fitness function is performed according to the deviation of the agricultural machinery's pose. In order to improve the efficiency of the algorithm, the inertia weight coefficient is improved. The particle swarm optimization (PSO) algorithm is used to determine the optimal look ahead distance in the pure pursuit model in real-time. The speed control function is constructed to control the variable speed of the agricultural machinery under different pose deviations.The prototype test results show that the average deviation is 24.4 cm, the average steady-state deviation is 4.3 cm, the average navigation time is 13.2 s, and the average stable distance is 318.1 cm when the linear path is tracked in the three initial states. The various indicators of path tracking are better than the constant speed and fixed line-of-sight test under the same conditions. The method proposed in this study has a good path tracking effect and can meet the needs of agricultural machinery for automatic navigation operations in the greenhouse.

Key words: agricultural machinery, particle swarm optimization, pure pursuit, dynamic look ahead distance, path tracking

中图分类号:

柴善鹏, 姚立健, 徐丽君, 陈钦汉, 徐涛涛, 杨岩坤. 基于动态前视距离纯追踪模型的温室农机路径跟踪研究^*[J]. 中国农机化学报, 2021, 42(11): 58-64.

Chai Shanpeng, Yao Lijian, Xu Lijun, Chen Qinhan, Xu Taotao, Yang Yankun. Research on greenhouse agricultural machinery path tracking based on dynamic look ahead distance pure pursuit model[J]. Journal of Chinese Agricultural Mechanization, 2021, 42(11): 58-64.

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基于动态前视距离纯追踪模型的温室农机路径跟踪研究^*

Research on greenhouse agricultural machinery path tracking based on dynamic look ahead distance pure pursuit model

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