AGRO是能自主巡田的智能农用机器人，可实时感知环境并估算开心果产量。
AGRO: An Autonomous AI Rover for Precision Agriculture
- 融合机器学习与视觉技术，实现自主导航与避障。
- 能实时建图、定位，并估算开心果产量。
- 适合需要精准农业数据的农场主和研究者使用。
无人地面车辆（UGVs）正成为精准农业中的关键工具。结合机器学习，可解决多种复杂农业问题。本研究开发了一款名为AGRO（自主地面探测车）的UGV，能够自主穿越农田并采集数据。AGRO利用机器学习、计算机视觉及其他传感器技术，实现自我定位、实时环境地图构建，并完成开心果产量估算。该研究旨在自动化耗时操作，帮助农民做出数据驱动的决策。此外，AGRO为先进机器学习方法提供了数据基础，持续捕捉真实世界信息。
原文摘要 · Abstract (English)
Unmanned Ground Vehicles (UGVs) are emerging as a crucial tool in the world of precision agriculture. The combination of UGVs with machine learning allows us to find solutions for a range of complex agricultural problems. This research focuses on developing a UGV capable of autonomously traversing agricultural fields and capturing data. The project, known as AGRO (Autonomous Ground Rover Observer) leverages machine learning, computer vision and other sensor technologies. AGRO uses its capabilities to determine pistachio yields, performing self-localization and real-time environmental mapping while avoiding obstacles. The main objective of this research work is to automate resource-consuming operations so that AGRO can support farmers in making data-driven decisions. Furthermore, AGRO provides a foundation for advanced machine learning techniques as it captures the world around it.
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