水果采摘机械臂的开发挑战:批判性评述

Abdul Kaleem, Saddam Hussain, Muhammad Aqib, M. J. M. Cheema, S. Saleem, Umar Farooq
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引用次数: 0

摘要

在当前充满挑战的环境下,由于缺乏熟练劳动力、成本高昂和劳动力短缺,对人工耕作的需求日益减少,因此必须在农业领域促进先进技术的研发,以提高产量。在过去二十年里,对水果收割机技术(即机械化收割、有人和无人驾驶航空系统以及机器人技术)的需求不断增加。然而,一些行业正致力于开发低成本、工业规模生产的先进采收技术,但迄今为止,还没有开发出用于选择性采收珍贵水果和蔬菜的商业机械臂,尤其是在受控严格环境下,即温室和水培环境下。这篇研究文章的重点是开发自动机械臂的所有参数。文章广泛回顾了过去二十年(2000 年至 2022 年)的相关研究工作,包括其局限性和性能。在本研究中,根据综述的主题和范围,从不同来源获取数据。撰写本综述论文的一些常见数据来源包括同行评审期刊、书籍章节和谷歌学术上的会议论文集。对水果收割机的整体要求包括机械运动的机械手、定位和识别水果的视觉系统以及用于分离目的的末端执行器。这项工作总结了几项开发成果在收获时间、收获精度和检测效率方面的性能。据观察,提高收割效率和定制设计末端执行器是研究人员感兴趣的主要领域。通过在视觉系统中实施可获得较低识别错误率的最佳技术,可提高系统的收割效率。
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Development Challenges of Fruit-Harvesting Robotic Arms: A Critical Review
Promotion of research and development in advanced technology must be implemented in agriculture to increase production in the current challenging environment where the demand for manual farming is decreasing due to the unavailability of skilled labor, high cost, and shortage of labor. In the last two decades, the demand for fruit harvester technologies, i.e., mechanized harvesting, manned and unmanned aerial systems, and robotics, has increased. However, several industries are working on the development of industrial-scale production of advanced harvesting technologies at low cost, but to date, no commercial robotic arm has been developed for selective harvesting of valuable fruits and vegetables, especially within controlled strictures, i.e., greenhouse and hydroponic contexts. This research article focused on all the parameters that are responsible for the development of automated robotic arms. A broad review of the related research works from the past two decades (2000 to 2022) is discussed, including their limitations and performance. In this study, data are obtained from various sources depending on the topic and scope of the review. Some common sources of data for writing this review paper are peer-reviewed journals, book chapters, and conference proceedings from Google Scholar. The entire requirement for a fruit harvester contains a manipulator for mechanical movement, a vision system for localizing and recognizing fruit, and an end-effector for detachment purposes. Performance, in terms of harvesting time, harvesting accuracy, and detection efficiency of several developments, has been summarized in this work. It is observed that improvement in harvesting efficiency and custom design of end-effectors is the main area of interest for researchers. The harvesting efficiency of the system is increased by the implementation of optimal techniques in its vision system that can acquire low recognition error rates.
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