{"title":"一种改进的拖拉机自动导航纯追踪算法","authors":"Qiang Fu, Xiang Liu, Xueyin Liu, Gonglei Liao","doi":"10.1109/ICISCAE52414.2021.9590785","DOIUrl":null,"url":null,"abstract":"In this paper, an improved pure pursuit (IPP) for tractor autonomous navigation is proposed. The kinematics model is based on simplified two wheeled vehicle Ackermann model. By detecting the trend of deviation to the planned path, the looking-ahead distance, a key parameter in the pure tracking algorithm, is automatically adjusted to improve the accuracy of tracking the planned path. The simulation and field test show that the new method has higher accuracy and is easy to implement.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Pure Pursuit Algorithm for Tractor Automatic Navigation\",\"authors\":\"Qiang Fu, Xiang Liu, Xueyin Liu, Gonglei Liao\",\"doi\":\"10.1109/ICISCAE52414.2021.9590785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an improved pure pursuit (IPP) for tractor autonomous navigation is proposed. The kinematics model is based on simplified two wheeled vehicle Ackermann model. By detecting the trend of deviation to the planned path, the looking-ahead distance, a key parameter in the pure tracking algorithm, is automatically adjusted to improve the accuracy of tracking the planned path. The simulation and field test show that the new method has higher accuracy and is easy to implement.\",\"PeriodicalId\":115061,\"journal\":{\"name\":\"International Conference on Information Systems and Computer Aided Education\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Information Systems and Computer Aided Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE52414.2021.9590785\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Information Systems and Computer Aided Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE52414.2021.9590785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Pure Pursuit Algorithm for Tractor Automatic Navigation
In this paper, an improved pure pursuit (IPP) for tractor autonomous navigation is proposed. The kinematics model is based on simplified two wheeled vehicle Ackermann model. By detecting the trend of deviation to the planned path, the looking-ahead distance, a key parameter in the pure tracking algorithm, is automatically adjusted to improve the accuracy of tracking the planned path. The simulation and field test show that the new method has higher accuracy and is easy to implement.
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