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Actuators and sensors for application in agricultural robots: A review

Xie, D., Chen, L., Liu, L., Chen, L. and Wang, H.ORCID: 0000-0003-2789-9530 (2022) Actuators and sensors for application in agricultural robots: A review. Machines, 10 (10). Article 913.

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Abstract

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future.

Item Type: Journal Article
Murdoch Affiliation(s): Engineering and Energy
Centre for Water, Energy and Waste
Harry Butler Institute
Publisher: MDPI
Copyright: © 2022 by the authors
URI: http://researchrepository.murdoch.edu.au/id/eprint/66510
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