期刊
ROBOTICS
卷 10, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/robotics10020052
关键词
agricultural robots; agriculture 4.0; precision agriculture
类别
资金
- National Funds through the Portuguese funding agency, FCT-Fundacao para a Ciencia e a Tecnologia [UIDB/50014/2020]
The constant development of agricultural robotics aims to address challenges posed by population growth, urbanization, product competitiveness, environmental preservation, and a lack of qualified labor. This paper reviews the main applications of agricultural robotic systems and highlights the four major areas for future research work in enhancing smart agriculture: locomotion systems, sensors, computer vision algorithms, and communication technologies.
The constant advances in agricultural robotics aim to overcome the challenges imposed by population growth, accelerated urbanization, high competitiveness of high-quality products, environmental preservation and a lack of qualified labor. In this sense, this review paper surveys the main existing applications of agricultural robotic systems for the execution of land preparation before planting, sowing, planting, plant treatment, harvesting, yield estimation and phenotyping. In general, all robots were evaluated according to the following criteria: its locomotion system, what is the final application, if it has sensors, robotic arm and/or computer vision algorithm, what is its development stage and which country and continent they belong. After evaluating all similar characteristics, to expose the research trends, common pitfalls and the characteristics that hinder commercial development, and discover which countries are investing into Research and Development (R&D) in these technologies for the future, four major areas that need future research work for enhancing the state of the art in smart agriculture were highlighted: locomotion systems, sensors, computer vision algorithms and communication technologies. The results of this research suggest that the investment in agricultural robotic systems allows to achieve short-harvest monitoring-and long-term objectives-yield estimation.
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