Saved in:
Bibliographic Details
Main Authors: Yang, Teaya, Ibrahimov, Roman, Mueller, Mark W.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.18293
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913843204063232
author Yang, Teaya
Ibrahimov, Roman
Mueller, Mark W.
author_facet Yang, Teaya
Ibrahimov, Roman
Mueller, Mark W.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2409_18293
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Towards Safe and Efficient Through-the-Canopy Autonomous Fruit Counting with UAVs
Yang, Teaya
Ibrahimov, Roman
Mueller, Mark W.
Robotics
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.
title Towards Safe and Efficient Through-the-Canopy Autonomous Fruit Counting with UAVs
topic Robotics
url https://arxiv.org/abs/2409.18293