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Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead

Title
Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead
Type
Another Publication in an International Scientific Journal
Year
2021
Authors
Oliveira, LFP
(Author)
Other
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Silva, MF
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. View Authenticus page Without ORCID
Journal
Title: RoboticsImported from Authenticus Search for Journal Publications
Vol. 10
Final page: 52
Publisher: MDPI
Indexing
Other information
Authenticus ID: P-00T-NY5
Abstract (EN): 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.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 31
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