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Article(id=1325194278414201568, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1325194266577875587, articleNumber=null, orderNo=null, doi=10.12398/j.issn.2096-7217.2023.03.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1685721600000, receivedDateStr=2023-06-03, revisedDate=1690992000000, revisedDateStr=2023-08-03, acceptedDate=null, acceptedDateStr=null, onlineDate=1793880536893, onlineDateStr=2026-11-05, pubDate=1692028800000, pubDateStr=2023-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793880536893, onlineIssueDateStr=2026-11-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793880536893, creator=13701087609, updateTime=1793880536893, updator=13701087609, issue=Issue{id=1325194266577875587, tenantId=1146029695717560320, journalId=1319690209941618849, year='2023', volume='4', issue='3', pageStart='1', pageEnd='70', issueExtLink='null', onlineDate='null', pubDate='1692028800000', pubDateStr='2023-08-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793880534070, creator='13701087609', updateTime=1793880534070, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=24, endPage=31, ext={EN=ArticleExt(id=1325194278749745889, articleId=1325194278414201568, tenantId=1146029695717560320, journalId=1319690209941618849, language=EN, title=Integration of geometric-based path tracking controller and its application in agricultural machinery automatic navigation, columnId=null, journalTitle=Journal of Intelligent Agricultural Mechanization, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Agricultural machinery autonomous navigation is an effective approach to achieve precision agriculture, and high-precision path tracking control is a critical assurance for the reliability of intelligent agricultural machinery autonomous operations. To improve the adaptability of path tracking algorithms under different path curvatures and initial error conditions, a geometric path tracking combined algorithm based on adaptive switching of two geometric path tracking methods was proposed. The steady-state errors and convergence characteristics of the pure pursuit (PP) and Stanley model in U-shaped path tracking were analyzed, and their optimal geometric path tracking parameters were respectively set at a constant velocity. A path tracking method switching logic was designed based on tracking errors and path curvature as input, and a boustrophedon path was used to test the geometric path tracking combined algorithm. A mobile cart platform was built to verify the effectiveness of the proposed algorithm. The tracking results showed that when the initial error is 2.5 meters, the Stanley model had a faster convergence rate than the PP algorithm. When operating at speeds of 1.0 m/s for straight paths and 0.7 m/s for curved paths, the PP and Stanley model exhibited similar tracking errors for straight segments, but when the curvature changed abruptly, the maximum tracking errors for the PP and Stanley model were 12.0 cm and 11.0 cm respectively. The path tracking combined algorithm effectively reduced the tracking error during curvature changes, with a maximum tracking error of 9.0 cm under the same speed configuration for the reciprocating shuttle path, representing a reduction of 25.0% and 18.2% compared to the PP and Stanley model respectively. The integration of geometric-based path tracking algorithm reduced the computational load and complexity of online optimization for forward distance and gain coefficient, and thus effectively improved the adaptability of path tracking algorithms for agricultural machinery under complex soil condition.

, authors=Xinyu CUI1, Bingbo CUI1, 2, *, Zhen MA1, 2, Yi HAN1, Jianxin ZHANG1, Xinhua WEI1, 2, authorsList=Xinyu CUI, Bingbo CUI, Zhen MA, Yi HAN, Jianxin ZHANG, Xinhua WEI, authorCompany=null, correspAuthors=Bingbo CUI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1325194279106261730, articleId=1325194278414201568, tenantId=1146029695717560320, journalId=1319690209941618849, language=CN, title=几何路径跟踪组合算法及其农业机械自动导航应用, columnId=null, journalTitle=智能化农业装备学报（中英文）, columnName=, runingTitle=null, highlight=null, articleAbstract=

农业机械自动导航是实现精准农业的有效途径，高精度路径跟踪控制是智能农机自主作业可靠性的重要保证。为提高不同路径曲率和初始误差条件下路径跟踪算法适应性，基于两种几何路径跟踪方法自适应切换提出一种几何路径跟踪组合算法。分析纯追踪和Stanley模型在U型路径跟踪中的稳态误差和收敛特性，在恒定速度下分别设置其最优几何路径跟踪参数，以跟踪误差和路径曲率为输入量设计路径跟踪方法切换逻辑，并采用往复式梭行路径对几何路径跟踪组合算法进行测试。搭建移动小车平台对所提算法有效性进行验证，跟踪结果表明当初始误差为2.5 m时，Stanley模型较纯追踪算法有更快的收敛速度，当直线和曲线路径作业速度为1.0 m/s和0.7 m/s时，纯追踪与Stanley具有相似直线段跟踪误差，但曲率突变时纯追踪和Stanley模型最大跟踪误差分别为12.0 cm及11.0 cm。路径跟踪组合算法有效减小曲率突变时路径跟踪误差，相同速度配置下梭行路径最大跟踪误差为9.0 cm，较纯追踪和Stanley分别减小25.0%和18.2%。几何路径跟踪组合算法减少前视距离和增益系数在线优化运算量与算法复杂度，可为复杂作业场景下农机自适应路径跟踪算法设计提供工程实现参考。

, authors=崔鑫宇1, 崔冰波1, 2, *, 马振1, 2, 韩逸1, 张建鑫1, 魏新华1, 2, authorsList=崔鑫宇, 崔冰波, 马振, 韩逸, 张建鑫, 魏新华, authorCompany=null, correspAuthors=崔冰波, authorNote=

崔鑫宇，男，2000年生，黑龙江齐齐哈尔人，硕士研究生；研究方向为多机协同控制技术。E-mail：

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* 崔冰波，男，1986年生，安徽亳州人，博士，副研究员；研究方向为农机智能导航与自主作业技术。E-mail：
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崔鑫宇，男，2000年生，黑龙江齐齐哈尔人，硕士研究生；研究方向为多机协同控制技术。E-mail：

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崔鑫宇，男，2000年生，黑龙江齐齐哈尔人，硕士研究生；研究方向为多机协同控制技术。E-mail：

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几何路径跟踪组合算法及其农业机械自动导航应用
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崔鑫宇 1 , 崔冰波 1, 2, * , 马振 1, 2 , 韩逸 1 , 张建鑫 1 , 魏新华 1, 2
智能化农业装备学报（中英文） | 2023,4(3): 24-31
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智能化农业装备学报（中英文） | 2023 , 4 (3) : 24 -31
几何路径跟踪组合算法及其农业机械自动导航应用
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崔鑫宇1 , 崔冰波1, 2, * , 马振1, 2, 韩逸1, 张建鑫1, 魏新华1, 2
作者信息
  • 1.江苏大学农业工程学院，江苏 镇江，212013
  • 2.江苏大学现代农业装备与技术教育部重点实验室，江苏 镇江，212013
通讯作者:
* 崔冰波，男，1986年生，安徽亳州人，博士，副研究员；研究方向为农机智能导航与自主作业技术。E-mail：
作者简介:

崔鑫宇，男，2000年生，黑龙江齐齐哈尔人，硕士研究生；研究方向为多机协同控制技术。E-mail：

Integration of geometric-based path tracking controller and its application in agricultural machinery automatic navigation
Xinyu CUI1 , Bingbo CUI1, 2, * , Zhen MA1, 2, Yi HAN1, Jianxin ZHANG1, Xinhua WEI1, 2
Affiliations
  • 1.College of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
  • 2.Key Laboratory of Modern Agricultural Equipment and Technology of Ministry of Education, Jiangsu University, Zhenjiang 212013, China
出版时间: 2023-08-15 doi: 10.12398/j.issn.2096-7217.2023.03.003
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摘要
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农业机械自动导航是实现精准农业的有效途径，高精度路径跟踪控制是智能农机自主作业可靠性的重要保证。为提高不同路径曲率和初始误差条件下路径跟踪算法适应性，基于两种几何路径跟踪方法自适应切换提出一种几何路径跟踪组合算法。分析纯追踪和Stanley模型在U型路径跟踪中的稳态误差和收敛特性，在恒定速度下分别设置其最优几何路径跟踪参数，以跟踪误差和路径曲率为输入量设计路径跟踪方法切换逻辑，并采用往复式梭行路径对几何路径跟踪组合算法进行测试。搭建移动小车平台对所提算法有效性进行验证，跟踪结果表明当初始误差为2.5 m时，Stanley模型较纯追踪算法有更快的收敛速度，当直线和曲线路径作业速度为1.0 m/s和0.7 m/s时，纯追踪与Stanley具有相似直线段跟踪误差，但曲率突变时纯追踪和Stanley模型最大跟踪误差分别为12.0 cm及11.0 cm。路径跟踪组合算法有效减小曲率突变时路径跟踪误差，相同速度配置下梭行路径最大跟踪误差为9.0 cm，较纯追踪和Stanley分别减小25.0%和18.2%。几何路径跟踪组合算法减少前视距离和增益系数在线优化运算量与算法复杂度，可为复杂作业场景下农机自适应路径跟踪算法设计提供工程实现参考。

智能农业装备  /  农机自动导航  /  几何路径跟踪方法  /  Stanley模型  /  纯追踪算法

Agricultural machinery autonomous navigation is an effective approach to achieve precision agriculture, and high-precision path tracking control is a critical assurance for the reliability of intelligent agricultural machinery autonomous operations. To improve the adaptability of path tracking algorithms under different path curvatures and initial error conditions, a geometric path tracking combined algorithm based on adaptive switching of two geometric path tracking methods was proposed. The steady-state errors and convergence characteristics of the pure pursuit (PP) and Stanley model in U-shaped path tracking were analyzed, and their optimal geometric path tracking parameters were respectively set at a constant velocity. A path tracking method switching logic was designed based on tracking errors and path curvature as input, and a boustrophedon path was used to test the geometric path tracking combined algorithm. A mobile cart platform was built to verify the effectiveness of the proposed algorithm. The tracking results showed that when the initial error is 2.5 meters, the Stanley model had a faster convergence rate than the PP algorithm. When operating at speeds of 1.0 m/s for straight paths and 0.7 m/s for curved paths, the PP and Stanley model exhibited similar tracking errors for straight segments, but when the curvature changed abruptly, the maximum tracking errors for the PP and Stanley model were 12.0 cm and 11.0 cm respectively. The path tracking combined algorithm effectively reduced the tracking error during curvature changes, with a maximum tracking error of 9.0 cm under the same speed configuration for the reciprocating shuttle path, representing a reduction of 25.0% and 18.2% compared to the PP and Stanley model respectively. The integration of geometric-based path tracking algorithm reduced the computational load and complexity of online optimization for forward distance and gain coefficient, and thus effectively improved the adaptability of path tracking algorithms for agricultural machinery under complex soil condition.

intelligent agricultural equipment  /  automatic navigation of agricultural machinery  /  geometric-based path tracking  /  Stanley model  /  pure pursuit algorithm
崔鑫宇, 崔冰波, 马振, 韩逸, 张建鑫, 魏新华. 几何路径跟踪组合算法及其农业机械自动导航应用. 智能化农业装备学报（中英文）, 2023 , 4 (3) : 24 -31 . DOI: 10.12398/j.issn.2096-7217.2023.03.003
Xinyu CUI, Bingbo CUI, Zhen MA, Yi HAN, Jianxin ZHANG, Xinhua WEI. Integration of geometric-based path tracking controller and its application in agricultural machinery automatic navigation[J]. Journal of Intelligent Agricultural Mechanization, 2023 , 4 (3) : 24 -31 . DOI: 10.12398/j.issn.2096-7217.2023.03.003
基金
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  • 国家自然科学基金项目(32271999)
  • 江苏省重点研发计划项目(BE2021313)
  • 省部共建现代农业装备与技术协同创新中心资助项目(XTCX2009)
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2023年第4卷第3期
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doi: 10.12398/j.issn.2096-7217.2023.03.003
  • 接收时间：2023-06-03
  • 首发时间：2026-11-05
  • 出版时间：2023-08-15
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  • 收稿日期：2023-06-03
  • 修回日期：2023-08-03
基金
国家自然科学基金项目(32271999)
江苏省重点研发计划项目(BE2021313)
省部共建现代农业装备与技术协同创新中心资助项目(XTCX2009)
作者信息
    1.江苏大学农业工程学院，江苏 镇江，212013
    2.江苏大学现代农业装备与技术教育部重点实验室，江苏 镇江，212013

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* 崔冰波，男，1986年生，安徽亳州人，博士，副研究员；研究方向为农机智能导航与自主作业技术。E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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