Active Navigation System for a Rubber-Tapping Robot Based on Trunk Detection

Jiahao Fang, Yongliang Shi*, Jianhua Cao, Yao Sun, Weimin Zhang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

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.

源语言英语
文章编号3717
期刊Remote Sensing
15
15
DOI
出版状态已出版 - 8月 2023

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