Robotic System for Green Fruit Thinning in Apple Orchards

Project Overview

GNE22-285
Project Type: Graduate Student
Funds awarded in 2022: $14,941.00
Projected End Date: 07/31/2023
Grant Recipient: The Pennsylvania State University
Region: Northeast
State: Pennsylvania
Graduate Student:
Faculty Advisor:
Long He
Pennsylvania State University

Commodities

  • Fruits: apples

Practices

  • Crop Production: cropping systems

    Proposal abstract:

    Green fruit thinning is the process of removing young fruit from trees to increase the size of remaining fruit. Previous applications of robotic technologies in agriculture imply the feasibility of an automated green fruit thinning system, which could mitigate drawbacks present in more-traditional thinning methods, e.g., non-selective thinning, significant labor requirements, etc. In the proposed research project, a robotic green fruit thinning system will be developed and tested. The project will consist of four main objectives: 1) to develop a stem-cutting end-effector prototype based on garden snippers; 2) to develop a 3D vision system for detecting coordinates of target fruit and boundaries in point-cloud form in an orchard environment; and 3) to integrate the components developed in objectives 1 and 2, along with those developed prior to the project start date, to create a robotic green fruit thinning system. The expected outcome of this research project is the development of a robotic green fruit thinning system that satisfies the following criteria: 1) the machine vision system detects green fruit with high accuracy; 2) the end-effector removes green fruit in an optimal manner; 3) the end-effector does not remove incorrect fruit; 4) the robotic manipulator moves to its desired position in a timely manner; and 5) the tree is not damaged during thinning. It is expected that the developed system will serve as a proof of concept, showing the feasibility of robotic green fruit thinning systems, potentially motivating further development for commercial implementation, and ultimately, improving the profitability of orchard management.

    Project objectives from proposal:

    The primary goal of this project is the development of a robotic system for green fruit thinning. The following are the objectives for the project:

    Objective #1: Green Fruit Removal End-Effector Development

    An end-effector for green fruit thinning will be developed. Based on the results of prior green fruit removal dynamics experiments conducted by the project team members, a stem-cutting mechanism will be used for simplicity and effectiveness of design. The end-effector design will be based on garden snippers. The end-effector will be designed such that no unintended damage is caused to trees and their structures The performance of the end-effector will then be evaluated in orchard tests. The end-effector performance will be compared to that of a previous designed developed previously by the project team members. It is expected that the end-effector will thin green fruit with a high success rate, while causing no damage to the tree or unintended removal of non-target fruit.

    Objective #2: 3D Vision for Robotic Green Fruit Thinning

    A 3D vision system will be developed for this project. The primary purpose of the 3D vision system will be to determine the 3D coordinates of target green fruit and a boundary map for collision-free path planning. The 3D vision system will build on results obtained from deep learning-based computer vision algorithms implemented for robotic green fruit thinning by the project team members. Data obtained during Spring 2022 including RGB-D (color-depth) images will be used to aid in developing and implementing algorithms for 3D vision. A 3D vision system than can determine boundary points and fruit locations with high accuracy is expected.

    Objective #3: Robotic Green Fruit Thinning System

    A completed green fruit thinning system will be developed. The system will utilize the components developed for objectives #1 and #2 as well as components developed before the proposed project period. The end-effector will be mounted onto the robotic manipulator present in the lab facilities used for this project. The vision system will be used, as described in Objective #2, to determine target fruit locations and boundaries for the robotic manipulator to navigate. Path planning algorithms developed before the project start period will be used to determine the shortest path between multiple fruit. The performance of the system will be evaluated in orchard tests. A system that thins green fruit from a tree with high accuracy and success with no collisions with obstacles is expected.

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.