Lei Liu , Fan Yang , Xiangyi Liu, Yuefeng Du, Xiaoyu Li, Guorun Li, Du Chen, Zhongxiang Zhu, Zhenghe Song
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Secondly, we searched and screened 678 relevant literature from electronic databases such as Science Direct, Web of Science, etc., and quantitatively analyzed all the literature in terms of three dimensions: year of publication, country, and keywords. Then, we systematically provided the current research status of ploughing-seeding, weeding, monitoring, harvesting, and information-gathering, crop protection and agricultural fly robots. Furthermore, the global development of field robots shows a trend of rapid growth and technology upgrading, and we proposed the common key technologies of field robots, including intelligent sensing, smart decision-making and control, dexterous arm and hand operation, autonomous and stable walking, and Cloud-Edge-End fusion intelligent operation. Finally, we summarized the challenges faced by robots, such as low sensing accuracy, poor operability, and low operating efficiency. 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引用次数: 0
摘要
工业革命 4.0 的到来,以及人工智能(AI)、云计算和物联网(IoT)的快速发展,引发了一场新的农业技术革命。田间机器人作为农业机器人的重要分支,在保障粮食安全、抢占全球农业制高点、实现农业可持续发展等方面具有不可替代的作用。在本研究中,我们首先明确了田间机器人的定义,并回顾了农业机器人的不同发展阶段。其次,我们从 Science Direct、Web of Science 等电子数据库中检索和筛选了 678 篇相关文献,并从发表年份、国家和关键词三个维度对所有文献进行了定量分析。然后,我们系统地介绍了犁地-播种、除草、监测、收割以及信息采集、作物保护和农业飞防机器人的研究现状。此外,全球田间机器人的发展呈现出快速增长和技术升级的趋势,我们提出了田间机器人的共性关键技术,包括智能感知、智能决策与控制、灵巧的手臂和手部操作、自主稳定行走、云-端融合智能操作等。最后,我们总结了机器人面临的挑战,如传感精度低、可操作性差、运行效率低等。因此,我们试图为野外机器人的未来发展提供新的机遇,如非结构化信息分析、5G、人工智能、数字双胞胎、机器人群协作等新技术,从而实现全自主感知的野外作业场景。
A review of the current status and common key technologies for agricultural field robots
The arrival of the Industrial Revolution 4.0 and the quick advancement of artificial intelligence (AI), cloud computing, and internet of things (IoT) have led to the beginning of a new technological revolution in agriculture. As an important branch of agricultural robots, field robots have an irreplaceable role in guaranteeing food security, seizing the global agricultural high ground, and realizing sustainable agricultural development. In this study, we first clarified the definition of field robots and review the different development stages of agricultural robots. Secondly, we searched and screened 678 relevant literature from electronic databases such as Science Direct, Web of Science, etc., and quantitatively analyzed all the literature in terms of three dimensions: year of publication, country, and keywords. Then, we systematically provided the current research status of ploughing-seeding, weeding, monitoring, harvesting, and information-gathering, crop protection and agricultural fly robots. Furthermore, the global development of field robots shows a trend of rapid growth and technology upgrading, and we proposed the common key technologies of field robots, including intelligent sensing, smart decision-making and control, dexterous arm and hand operation, autonomous and stable walking, and Cloud-Edge-End fusion intelligent operation. Finally, we summarized the challenges faced by robots, such as low sensing accuracy, poor operability, and low operating efficiency. Therefore, we attempted to provide new opportunities for the future development of field robots, such as new technologies such as unstructured information analysis, 5G, AI, digital twins, robots swarms collaboration, and other technologies, which enable the realization of field operation scenarios with fully autonomous perception.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.