无人机果园果实计数系统实现安全高效穿冠作业
Towards Safe and Efficient Through-the-Canopy Autonomous Fruit Counting with UAVs
- 构建高保真仿真优化飞行路径，适应复杂树冠环境
- 低成本自主系统实现树冠层精准导航与图像采集
- 基于RGB图像的鲁棒果实检测流程，支持自动化计数
我们提出一种用于大规模果园中安全高效穿冠果实计数的自主飞行系统。由于果园布局、树冠密度和植株变异导致飞行路径需精细调优，传统飞越树冠上方的航拍方式易受叶片枝条遮挡，而穿冠飞行虽可减少遮挡但面临更复杂的密闭环境挑战。本系统通过三项集成技术应对：(i) 高保真仿真框架以优化飞行轨迹；(ii) 低成本自主导航栈实现树冠层级飞行与数据采集；(iii) 基于RGB图像的鲁棒果实检测与计数工作流。通过使用树冠层航空图像进行果实计数，并验证实验平台的自主导航能力，证明了该系统的有效性。
原文摘要 · Abstract (English)
We present an autonomous aerial system for safe and efficient through-the-canopy fruit counting. Aerial robot applications in large-scale orchards face significant challenges due to the complexity of fine-tuning flight paths based on orchard layouts, canopy density, and plant variability. Through-the-canopy navigation is crucial for minimizing occlusion by leaves and branches but is more challenging due to the complex and dense environment compared to traditional over-the-canopy flights. Our system addresses these challenges by integrating: i) a high-fidelity simulation framework for optimizing flight trajectories, ii) a low-cost autonomy stack for canopy-level navigation and data collection, and iii) a robust workflow for fruit detection and counting using RGB images. We validate our approach through fruit counting with canopy-level aerial images and by demonstrating the autonomous navigation capabilities of our experimental vehicle.
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