Chenming Hu , Yu Ru , Xianzhe Li , Shuping Fang , Hongping Zhou , Xianghai Yan , Mengnan Liu , Rong Xie
{"title":"基于改进型纯追随算法的制动转向履带式车辆路径跟踪控制","authors":"Chenming Hu , Yu Ru , Xianzhe Li , Shuping Fang , Hongping Zhou , Xianghai Yan , Mengnan Liu , Rong Xie","doi":"10.1016/j.biosystemseng.2024.04.006","DOIUrl":null,"url":null,"abstract":"<div><p>Path tracking is critical for agricultural vehicles to achieve autonomous operation and to improve operational efficiency and accuracy. This study aims to address the high-precision path tracking requirements for the tracked vehicle GY-8. An improved pure pursuit path tracking control method is proposed to enhance the performance of path tracking. For the GY-8 vehicle's single-sided braking and steering approach, a dual-wheel differential kinematic model is established. A smooth steering method using PWM (Pulse Width Modulation) is designed to reduce the likelihood of deviation from the predetermined path due to PWM braking steering. A method based on the theory of circular arc similarity is introduced to determine the path curvature and segmentation. The NSGA-II optimisation algorithm is employed to optimise and obtain the optimal look-ahead distance for different curvature segments, thereby enhancing the accuracy of path tracking. The improved algorithm was experimentally validated for path tracking on paved surfaces. In the experiments, the improved algorithm demonstrated average error, maximum error, error standard deviation, and Fréchet distance of 0.0266 m, 0.0973 m, 0.0195 m, and 0.0891 m, respectively. This represents a 15.6%, 25.8%, 4.9%, and 27.6% improvement over the pure tracking algorithm. When applying the improved pure tracking algorithm to path tracking in agricultural orchard soil environments, the results indicated maximum error, average error, and error standard deviation of 0.1272 m, 0.0351 m, and 0.0215 m, respectively. The overall findings suggest that the improved method significantly enhances the accuracy of path tracking, providing theoretical support for advancing navigation technology in tracked vehicles.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Path tracking control for brake-steering tracked vehicles based on an improved pure pursuit algorithm\",\"authors\":\"Chenming Hu , Yu Ru , Xianzhe Li , Shuping Fang , Hongping Zhou , Xianghai Yan , Mengnan Liu , Rong Xie\",\"doi\":\"10.1016/j.biosystemseng.2024.04.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Path tracking is critical for agricultural vehicles to achieve autonomous operation and to improve operational efficiency and accuracy. This study aims to address the high-precision path tracking requirements for the tracked vehicle GY-8. An improved pure pursuit path tracking control method is proposed to enhance the performance of path tracking. For the GY-8 vehicle's single-sided braking and steering approach, a dual-wheel differential kinematic model is established. A smooth steering method using PWM (Pulse Width Modulation) is designed to reduce the likelihood of deviation from the predetermined path due to PWM braking steering. A method based on the theory of circular arc similarity is introduced to determine the path curvature and segmentation. The NSGA-II optimisation algorithm is employed to optimise and obtain the optimal look-ahead distance for different curvature segments, thereby enhancing the accuracy of path tracking. The improved algorithm was experimentally validated for path tracking on paved surfaces. In the experiments, the improved algorithm demonstrated average error, maximum error, error standard deviation, and Fréchet distance of 0.0266 m, 0.0973 m, 0.0195 m, and 0.0891 m, respectively. This represents a 15.6%, 25.8%, 4.9%, and 27.6% improvement over the pure tracking algorithm. When applying the improved pure tracking algorithm to path tracking in agricultural orchard soil environments, the results indicated maximum error, average error, and error standard deviation of 0.1272 m, 0.0351 m, and 0.0215 m, respectively. The overall findings suggest that the improved method significantly enhances the accuracy of path tracking, providing theoretical support for advancing navigation technology in tracked vehicles.</p></div>\",\"PeriodicalId\":9173,\"journal\":{\"name\":\"Biosystems Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosystems Engineering\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1537511024000795\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1537511024000795","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
Path tracking control for brake-steering tracked vehicles based on an improved pure pursuit algorithm
Path tracking is critical for agricultural vehicles to achieve autonomous operation and to improve operational efficiency and accuracy. This study aims to address the high-precision path tracking requirements for the tracked vehicle GY-8. An improved pure pursuit path tracking control method is proposed to enhance the performance of path tracking. For the GY-8 vehicle's single-sided braking and steering approach, a dual-wheel differential kinematic model is established. A smooth steering method using PWM (Pulse Width Modulation) is designed to reduce the likelihood of deviation from the predetermined path due to PWM braking steering. A method based on the theory of circular arc similarity is introduced to determine the path curvature and segmentation. The NSGA-II optimisation algorithm is employed to optimise and obtain the optimal look-ahead distance for different curvature segments, thereby enhancing the accuracy of path tracking. The improved algorithm was experimentally validated for path tracking on paved surfaces. In the experiments, the improved algorithm demonstrated average error, maximum error, error standard deviation, and Fréchet distance of 0.0266 m, 0.0973 m, 0.0195 m, and 0.0891 m, respectively. This represents a 15.6%, 25.8%, 4.9%, and 27.6% improvement over the pure tracking algorithm. When applying the improved pure tracking algorithm to path tracking in agricultural orchard soil environments, the results indicated maximum error, average error, and error standard deviation of 0.1272 m, 0.0351 m, and 0.0215 m, respectively. The overall findings suggest that the improved method significantly enhances the accuracy of path tracking, providing theoretical support for advancing navigation technology in tracked vehicles.
期刊介绍:
Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.