Autonomous Apple Fruitlet Sizing and Growth Rate Tracking using Computer Vision
Overview
This paper introduces a computer vision system that uses stereo camera images to segment, cluster, and fit ellipses to apple fruitlets for diameter measurement. By associating clusters across days, the system calculates growth rates. Quantitative results from an apple orchard show prediction of abscission rates within 3.5% of the current caliper method with a sixfold speedup and significantly less manual effort. Results also include images captured by a robotic system in the field, with discussion of steps needed for full autonomy.
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“uantitative results on data collected in an apple orchard, and demonstrate that our system is able to predict abscise rates within 3.5% of the current method with a 6 times improvement in speed, while requiring significantly less manual effort. Moreover, we provide results on images captured by a robotic system in the field, and discuss the next steps required to make the process fully autonomous.”
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- arXiv Robotics — research abstractsSignalAutonomous Apple Fruitlet Sizing and Growth Rate Tracking using Computer Vision
This paper introduces a computer vision system that uses stereo camera images to segment, cluster, and fit ellipses to apple fruitlets for diameter measurement. By associating clusters across days, the system calculates growth rates. Quantitative results from an apple orchard show prediction of abscission rates within 3.5% of the current caliper method with a sixfold speedup and significantly less manual effort. Results also include images captured by a robotic system in the field, with discussion of steps needed for full autonomy.
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