Towards Safe and Efficient Through-the-Canopy Autonomous Fruit Counting with UAVs

TL;DR

This paper introduces an autonomous UAV system designed for safe, efficient through-the-canopy fruit counting in orchards, combining simulation, low-cost navigation, and robust fruit detection methods.

Contribution

It presents a novel integrated system that addresses the challenges of through-the-canopy navigation and fruit counting, including a simulation framework and a low-cost autonomy stack.

Findings

Successful autonomous navigation in complex orchard environments

Accurate fruit counting from canopy-level aerial images

Validated system performance through real-world experiments

Abstract

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.