Design and Field Evaluation of an End Effector for Robotic Strawberry Harvesting

Author:

Ochoa Ezekyel1,Mo Changki1

Affiliation:

1. School of Engineering and Applied Sciences, Washington State University Tri-Cities, Richland, WA 99354, USA

Abstract

As the world’s population continues to rise while the agricultural workforce declines, farmers are increasingly challenged to meet the growing food demand. Strawberries grown in the U.S. are especially threatened by such stipulations, as the cost of labor for such a delicate crop remains the bulk of the total production costs. Autonomous systems within the agricultural sector have enormous potential to catalyze the labor and land expansions required to meet the demands of feeding an increasing population, as well as heavily reducing the amount of food waste experienced in open fields. Our team is working to enhance robotic solutions for strawberry production, aiming to improve field processes and better replicate the efficiency of human workers. We propose a modular configuration that includes a Delta X parallel robot and a pneumatically powered end effector designed for precise strawberry harvesting. Our primary focus is on optimizing the design of the end effector and validating its high-speed actuation capabilities. The prototype of the presented end effector achieved high success rates of 94.74% in simulated environments and 100% in strawberry fields at Farias Farms, even when tasked to harvest in the densely covered conditions of the late growing season. Using an off-the-shelf robotic configuration, the system’s workspace has been validated as adequate for harvesting in a typical two-plant-per-row strawberry field, with the hardware itself being evaluated to harvest each strawberry in 2.8–3.8 s. This capability sets the stage for future enhancements, including the integration of the machine vision processes such that the system will identify and pick each strawberry within 5 s.

Funder

National Science Foundation (NSF) SBIR Phase I through Abberit

Publisher

MDPI AG

Reference39 articles.

1. United Nations Department of Economic and Social Affairs (2024, June 10). World Population Projected to Reach 9.8 Billion in 2050, and 11.2 Billion in 2100. Available online: https://www.un.org/en/desa/world-population-projected-reach-98-billion-2050-and-112-billion-2100.

2. GMI Research (2023, October 14). Agricultural Robots Market Size, Share & Industry Analysis 2029. Available online: https://www.gmiresearch.com/report/global-agricultural-robots-market/.

3. Robotics and Automation in Agriculture: Present and Future Applications;Mahmud;Appl. Model. Simul.,2020

4. Grand View Research (2024, June 12). Agricultural Robots Market Size, Share & Growth Report 2030. Available online: https://www.grandviewresearch.com/industry-analysis/agricultural-robots-market.

5. United States Department of Agriculture (2024, May 07). National Agricultural Statistics Service. Noncitrus Fruits and Nuts, Available online: https://usda.library.cornell.edu/concern/publications/zs25x846c.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.7亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2025 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3