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Towards automated canopy and crop-load management in tree fruit

Author: Manoj Karkee, George Kantor and Abhisesh Silwal, Mathew Whiting

Published: 2022

Summary: The widespread adoption of robotic harvesting systems requires deliberate canopy management to grow fruit in easily accessible locations. Therefore, it is necessary to automate canopy management in tree fruit so that labor use can be minimized throughout the entire production process. Specifically, this project focused on the automated pruning of fruit trees. The objectives of this project were to: i) Formulate objective pruning rules by integrating pruning strategy desirable for robotic/automated harvesting and the strategy currently used by growers in fruiting wall apple (e.g. formally trained) and cherry (e.g. UFO) orchards; ii) Develop a machine vision system to locate pruning branches in those two crop architectures; and iii) Integrate and evaluate a robotic pruning machine.

Keywords:

  • Technology
  • Automated pruning
  • Deep learning
  • Machine vision
  • Pruning robot
  • Robotics
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