Unverified paper record
A Ground Mobile Robot for Autonomous Terrestrial Laser Scanning-Based Field Phenotyping
arXiv · 5 Apr 2024 · 10.48550/arxiv.2404.04404
Abstract
Traditional field phenotyping methods are often manual, time-consuming, and destructive, posing a challenge for breeding progress. To address this bottleneck, robotics and automation technologies offer efficient sensing tools to monitor field evolution and crop development throughout the season. This study aimed to develop an autonomous ground robotic system for LiDAR-based field phenotyping in plant breeding trials. A Husky platform was equipped with a high-resolution three-dimensional (3D) laser scanner to collect in-field terrestrial laser scanning (TLS) data without human intervention. To automate the TLS process, a 3D ray casting analysis was implemented for optimal TLS site planning, and a route optimization algorithm was utilized to minimize travel distance during data collection. The platform was deployed in two cotton breeding fields for evaluation, where it autonomously collected TLS data. The system provided accurate pose information through RTK-GNSS positioning and sensor fusion techniques, with average errors of less than 0.6 cm for location and 0.38$^{\circ}$ for heading. The achieved localization accuracy allowed point cloud registration with mean point errors of approximately 2 cm, comparable to traditional TLS methods that rely on artificial targets and manual sensor deployment. This work presents an autonomous phenotyping platform that facilitates the quantitative assessment of plant traits under field conditions of both large agricultural fields and small breeding trials to contribute to the advancement of plant phenomics and breeding programs.
Plant phenotyping relevance
自律走行ロボットとLiDAR/TLSによる圃場フェノタイピング基盤を開発・評価しており、植物形質を定量評価するための取得・解析手法が研究の中心である。
abstractThis study aimed to develop an autonomous ground robotic system for LiDAR-based field phenotyping in plant breeding trials.
abstractThis work presents an autonomous phenotyping platform that facilitates the quantitative assessment of plant traits under field conditions
Code and data availability
The paper describes an autonomous TLS phenotyping robot and field experiments, but the supplied blocks contain no authors' data, point cloud, or code deposit. The only URL (https://github.com/husky/husky) refers to the vendor's generic ROS packages for the Husky platform, not paper-specific assets; all other URLs are C
No evidence-backed public reproduction asset is currently recorded.
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