Liao Juan, Wang Yao, Yin Junnan, Bi Lingling, Zhang Shun, Huiyu Zhou, Zhu Dequan
{"title":"An Integrated Navigation Method Based on an Adaptive Federal Kalman Filter for a Rice Transplanter","authors":"Liao Juan, Wang Yao, Yin Junnan, Bi Lingling, Zhang Shun, Huiyu Zhou, Zhu Dequan","doi":"10.13031/TRANS.13682","DOIUrl":null,"url":null,"abstract":"Highlights A GPS/INS/VNS integrated navigation system to improve navigation accuracy. An adaptive federal Kalman filter with the adaptive information distribution factor to fuse navigation information. Detection of seedling row lines based on sub-regional feature points clustering. A modified rice transplanter as an automatic navigation experimental platform. In this study, a global positioning system (GPS)/inertial navigation system (INS)/visual navigation system (VNS)-integrated navigation method based on an adaptive federal Kalman filter (KF) was presented to improve positioning accuracy for rice transplanter operating in paddy field. The proposed method used GPS/VNS to aid INS and reduce the influence of the accumulated error of the INS on navigation accuracy. An adaptive federal KF algorithm was designed to fuse navigation information from different sensors. The information distribution factor of each local filter was obtained adaptively on the basis of its own error covariance matrix. Computer simulation and the transplanter test were conducted to verify the proposed method. Results showed that the proposed method could provide accurate and reliable navigation information outputs, and achieve better navigation performance compared with that of single GPS navigation and integrated method based traditional federal KF.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"43 1","pages":"389-399"},"PeriodicalIF":1.4000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions of the ASABE","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.13031/TRANS.13682","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 4
Abstract
Highlights A GPS/INS/VNS integrated navigation system to improve navigation accuracy. An adaptive federal Kalman filter with the adaptive information distribution factor to fuse navigation information. Detection of seedling row lines based on sub-regional feature points clustering. A modified rice transplanter as an automatic navigation experimental platform. In this study, a global positioning system (GPS)/inertial navigation system (INS)/visual navigation system (VNS)-integrated navigation method based on an adaptive federal Kalman filter (KF) was presented to improve positioning accuracy for rice transplanter operating in paddy field. The proposed method used GPS/VNS to aid INS and reduce the influence of the accumulated error of the INS on navigation accuracy. An adaptive federal KF algorithm was designed to fuse navigation information from different sensors. The information distribution factor of each local filter was obtained adaptively on the basis of its own error covariance matrix. Computer simulation and the transplanter test were conducted to verify the proposed method. Results showed that the proposed method could provide accurate and reliable navigation information outputs, and achieve better navigation performance compared with that of single GPS navigation and integrated method based traditional federal KF.
期刊介绍:
This peer-reviewed journal publishes research that advances the engineering of agricultural, food, and biological systems. Submissions must include original data, analysis or design, or synthesis of existing information; research information for the improvement of education, design, construction, or manufacturing practice; or significant and convincing evidence that confirms and strengthens the findings of others or that revises ideas or challenges accepted theory.