{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:29:58Z","timestamp":1765960198902,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>High-precision position estimations of agricultural mobile robots (AMRs) are crucial for implementing control instructions. Although the global navigation satellite system (GNSS) and real-time kinematic GNSS (RTK-GNSS) provide high-precision positioning, the AMR accuracy decreases when the signals interfere with buildings or trees. An improved position estimation algorithm based on multisensor fusion and autoencoder neural network is proposed. The multisensor, RTK-GNSS, inertial-measurement-unit, and dual-rotary-encoder data are fused with Extended Kalman filter (EKF). To optimize the EKF noise matrix, the autoencoder and radial basis function (ARBF) neural network was used for modeling the state equation noise and EKF measurement equation. A multisensor AMR test platform was constructed for static experiments to estimate the circular error probability and twice-the-distance root-mean-squared criteria. Dynamic experiments were conducted on road, grass, and field environments. To validate the robustness of the proposed algorithm, abnormal working conditions of the sensors were tested on the road. The results showed that the positioning estimation accuracy was improved compared to the RTK-GNSS in all three environments. When the RTK-GNSS signal experienced interference or rotary encoders failed, the system could still improve the position estimation accuracy. The proposed system and optimization algorithm are thus significant for improving AMR position prediction performance.<\/jats:p>","DOI":"10.3390\/s22041522","type":"journal-article","created":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T21:36:24Z","timestamp":1645047384000},"page":"1522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2729-1165","authenticated-orcid":false,"given":"Peng","family":"Gao","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China"},{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"},{"name":"Interdisciplinary Program in Smart Agriculture, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"}]},{"given":"Hyeonseung","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"},{"name":"Interdisciplinary Program in Smart Agriculture, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"}]},{"given":"Chan-Woo","family":"Jeon","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea"}]},{"given":"Changho","family":"Yun","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea"},{"name":"Global Smart Farm Convergence Major, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea"}]},{"given":"Hak-Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea"},{"name":"Global Smart Farm Convergence Major, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea"},{"name":"Research Institute of Agriculture and Life Science, Seoul National University, Seoul 08826, Korea"}]},{"given":"Weixing","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China"}]},{"given":"Gaotian","family":"Liang","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China"}]},{"given":"Yufeng","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China"}]},{"given":"Zhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Smart Agriculture System Integration, Ministry of Education, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Agriculture Information Acquisition Technology, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100083, China"}]},{"given":"Xiongzhe","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"},{"name":"Interdisciplinary Program in Smart Agriculture, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.biosystemseng.2016.06.014","article-title":"Agricultural Robots for Field Operations: Concepts and Components","volume":"149","author":"Bechar","year":"2016","journal-title":"Biosyst. 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