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Season-robust localization for autonomous robot in orchard using two-stage LiDAR points segmentation with sensor fusion
http://hdl.handle.net/2241/0002024936
http://hdl.handle.net/2241/0002024936364132c1-3168-4bc4-8c32-9ee2757b5e14
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
SAT_14_102210.pdf (20.2 MB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||||
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| 公開日 | 2026-07-08 | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | Season-robust localization for autonomous robot in orchard using two-stage LiDAR points segmentation with sensor fusion | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| 資源タイプ | ||||||||||||||
| 資源タイプ | journal article | |||||||||||||
| 著者 |
Pan Siyu
× Pan Siyu
× Hu Yaohua
× Ohya Akihisa
筑波大学研究者総覧
0000000940
× Yorozu Ayanori
筑波大学研究者総覧
0000004390
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| 著者情報 | ||||||||||||||
| 所属・氏名 | システム情報系; 大矢, 晃久; オオヤ, アキヒサ; Ohya, Akihisa | |||||||||||||
| 研究者総覧URL | https://trios.tsukuba.ac.jp/researcher/940 | |||||||||||||
| 著者情報 | ||||||||||||||
| 所属・氏名 | システム情報系; 萬, 礼応; ヨロズ, アヤノリ; Yorozu, Ayanori | |||||||||||||
| 研究者総覧URL | https://trios.tsukuba.ac.jp/researcher/4390 | |||||||||||||
| 抄録 | ||||||||||||||
| 内容記述 | A robust cross-season, multi-route localization framework is proposed for agricultural environments with significant seasonal variations. Based on intensity-calibrated maps constructed across four seasons, a two-stage point segmentation method is employed to extract geometrically salient features, which are then used as inputs for NDT-based scan matching. An extended Kalman filter (EKF) is further integrated to fuse IMU and odometry measurements, thereby improving localization stability. Experimental results obtained under different seasonal conditions and across three route types demonstrate that the proposed method achieves both high accuracy and real-time performance. Specifically, the method attains an absolute trajectory error (ATE) of <= 0.100 m, an absolute rotation error (ARE) of < 5 degrees, and average execution time of < 2.5 ms. The average ATE values across four seasons are 0.089 m, 0.092 m, and 0.091 m, while the corresponding average ARE values are 1.089 degrees, 1.132 degrees, and 1.218 degrees, and the average execution time cross four seasons are 1.755 ms, 1.134 ms, and 1.663 ms for structured, circular, and unstructured routes, respectively. Local evaluations during turning further demonstrate stable localization performance across both routes and seasons, with ATE ranging from 0.057 to 0.098 m and ARE ranging from 1.044 degrees to 3.709 degrees, indicating strong robustness under dynamic motion conditions. Compared with existing methods, the proposed framework significantly reduces localization errors and enhances robustness in seasonally varying agricultural environments. | |||||||||||||
| キーワード | ||||||||||||||
| 主題 | Localization; Point segmentation; Sensor fusion; NDT-scan matching | |||||||||||||
| 書誌情報 |
en : Smart Agricultural Technology 巻 14, p. 102210, 発行日 2026-08 |
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| EISSN | ||||||||||||||
| 収録物識別子 | 2772-3755 | |||||||||||||
| アクセス権 | ||||||||||||||
| アクセス権 | open access | |||||||||||||
| ライセンス | ||||||||||||||
| 権利情報 | Creative Commons Attribution 4.0 International | |||||||||||||
| 権利情報 | ||||||||||||||
| 権利情報 | © 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). | |||||||||||||
| 出版者情報 | ||||||||||||||
| 出版者名 | Elsevier | |||||||||||||
| 出版タイプ | ||||||||||||||
| 出版タイプ | VoR | |||||||||||||
| 出典 | ||||||||||||||
| 関連タイプ | isIdenticalTo | |||||||||||||
| 関連識別子 | https://doi.org/10.1016/j.atech.2026.102210 | |||||||||||||
| 謝辞・助成情報 | ||||||||||||||
| 内容記述 | This work was supported by JST SPRING, Grant Number JPMJSP2124 and JSPS KAKENHI Grant Number 25K07677. Additionally, the authors would like to thank the Tsukuba Plant Innovation Research Center (T-PIRC), University of Tsukuba, for providing facilities for conducting this research in its orchards. | |||||||||||||
| 研究課題番号 | ||||||||||||||
| 助成機関名 | 日本学術振興会 (JSPS) | |||||||||||||
| 助成機関名 | Japan Society for the Promotion of Science (JSPS) | |||||||||||||
| 研究課題番号 | 25K07677 | |||||||||||||
| 研究課題番号URI | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-25K07677/ | |||||||||||||
| 研究課題名 | 環境ドメイン変換による複雑環境下での移動ロボットナビゲーション | |||||||||||||
