{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T20:13:33Z","timestamp":1775852013994,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T00:00:00Z","timestamp":1690243200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Automotive Walking Technology (Beijing) Co., Ltd.","award":["1630022022005"],"award-info":[{"award-number":["1630022022005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To address the practical navigation issues of rubber-tapping robots, this paper proposes an active navigation system guided by trunk detection for a rubber-tapping robot. A tightly coupled sliding-window-based factor graph method is proposed for pose tracking, which introduces normal distribution transform (NDT) measurement factors, inertial measurement unit (IMU) pre-integration factors, and prior factors generated by sliding window marginalization. To actively pursue goals in navigation, a distance-adaptive Euclidean clustering method is utilized in conjunction with cylinder fitting and composite criteria screening to identify tree trunks. Additionally, a hybrid map navigation approach involving 3D point cloud map localization and 2D grid map planning is proposed to apply these methods to the robot. Experiments show that our pose-tracking approach obtains generally better performance in accuracy and robustness compared to existing methods. The precision of our trunk detection method is 93% and the recall is 87%. A practical validation is completed in robot rubber-tapping tasks of a real rubber plantation. The proposed method can guide the rubber-tapping robot in complex forest environments and improve efficiency.<\/jats:p>","DOI":"10.3390\/rs15153717","type":"journal-article","created":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T01:09:01Z","timestamp":1690333741000},"page":"3717","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Active Navigation System for a Rubber-Tapping Robot Based on Trunk Detection"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3429-7837","authenticated-orcid":false,"given":"Jiahao","family":"Fang","sequence":"first","affiliation":[{"name":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Automotive Walking Technology (Beijing) Co., Ltd., Beijing 100071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3086-729X","authenticated-orcid":false,"given":"Yongliang","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3415-6049","authenticated-orcid":false,"given":"Jianhua","family":"Cao","sequence":"additional","affiliation":[{"name":"Rubber Research Institute of Chinese Academy of Tropical Agricultural Sciences, Danzhou 571101, China"}]},{"given":"Yao","family":"Sun","sequence":"additional","affiliation":[{"name":"Automotive Walking Technology (Beijing) Co., Ltd., Beijing 100071, China"}]},{"given":"Weimin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,25]]},"reference":[{"key":"ref_1","first-page":"56","article-title":"Vision Servo Control Method and Tapping Experiment of Natural Rubber Tapping Robot","volume":"2","author":"Zhou","year":"2020","journal-title":"Smart Agric."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhang, C., Yong, L., Chen, Y., Zhang, S., Ge, L., Wang, S., and Li, W. 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