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Cited by 14Smart Agriculture and AIAgricultural Engineering and MechanizationRemote Sensing in Agriculture

Advancing Agricultural Practices: Analyzing the Role of Robotics in Corn Farming

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Moshayedi, A. J., Khan, A. S., Geng, K., Hu, J., Kolahdooz, A.·2025·International Journal of Engineering
DOI 10.5829/ije.2025.38.07a.07
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Abstract

The need for robots in corn farming arises from the complexity and labor-intensive nature of tasks such as planting, weeding, harvesting, and monitoring. Robots offer precision, efficiency, and data-driven decision-making, addressing challenges in resource management, crop health, and productivity to meet the demands of modern agriculture. In this paper, the current landscape of robotics in corn farming, exploring various robotic systems, their functionalities, and their potential impacts on agricultural practices were studied. Additionally, analyzing the benefits and challenges associated with the adoption of robotic technology in corn farming, considering factors such as cost, compatibility with existing infrastructure, and regulatory considerations. Furthermore, the future directions and opportunities for research and development in the field of agricultural robotics, emphasizing the need for interdisciplinary collaboration and innovation to maximize the benefits of robotic technology in corn farming and contribute to sustainable food production are being discussed. The primary focus of this article is to analyze the components and design features of robots employed in our corn fields. This analysis not only serves as a comparison tool for designers but also encourages the development of more diverse designs. The structure of robots in corn farming plays a crucial role in advancing agricultural practices by boosting efficiency, precision, adaptability, data collection capabilities, environmental sustainability, and safety standards.

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  • Swarm-based and bioinspired approaches enhance connectivity and sustain operations, as evidenced in agricultural systems with improved uptime.

    “Swarm-based and bioinspired approaches enhance connectivity, leveraging distributed coordination to sustain operations, as evidenced in agricultural systems with improved uptime [14].”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [14]

    The Swarm Robotics section says multiple robots can collaborate and communicate, and projects that improved autonomy could enable 24/7 operation. The Communication Systems section also describes connectivity for autonomous operation. Neither passage establishes a bioinspired approach or reports improved uptime in an agricultural system; the sustained operation is a future prospect, not a demonstrated result. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Fault-tolerant cooperative robotics faces significant barriers in scalability, computational complexity, and real-world validation.

    “Fault-tolerant cooperative robotics faces significant barriers in scalability, computational complexity, and real-world validation, as highlighted across the literature.”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [14]

    The Discussion and Table 2 in the Conclusion identify scalability across different farm sizes as a challenge for corn-farming robots. They do not establish barriers in computational complexity or real-world validation for fault-tolerant cooperative robotics; the Case Studies section instead describes field tests of individual robots. Page numbers were not provided in our copy. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Mechanical redundancy approaches face limitations such as a 20% mass increase affecting mobility or complex fabrication needs.

    “These approaches, while effective in predictable settings, face limitations such as a 20% mass increase affecting mobility [3] or complex fabrication needs [14].”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [14]

    The paper’s ‘Common Structure and Parts of Robot’ section discusses chassis materials, payloads, and mobility, but does not report a 20% mass increase or link one to reduced mobility. Searches for ‘20% mass increase affecting mobility’ and ‘mechanical redundancy mass weight mobility fabrication’ found no passage addressing that claim. The fabrication clause is attributed to [14], not this source. (LLM, conf=0.74)

    Experimental — accuracy not yet measured

  • Tensegrity-enhanced designs using a 0.5 stiffness coefficient improve energy efficiency in corn farming.

    “with tensegrityenhanced designs using a 0.5 stiffness coefficient improving energy efficiency in corn farming [14].”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [14]

    The Power Source section discusses fuel efficiency in hybrid systems, but does not connect it to tensegrity designs. Searches for tensegrity and a 0.5 stiffness coefficient found no passage in our copy addressing the claimed design or its effect on energy efficiency in corn farming. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

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Cites

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Cited by

Sorted by citations

Authors
Moshayedi, A. J., Khan, A. S., Geng, K., Hu, J., & Kolahdooz, A.
Affiliations
  • Jiangxi University of Science and Technology (CN)
  • Henan Agricultural University (CN)
  • Universitas Negeri Padang (ID)
ORCID
Venue
International Journal of Engineering
Publisher
International Digital Organization for Scientific Information (IDOSI)
Published
2025
Volume
38
Issue
7
Pages
1517-1532
ISSN
  • 1025-2495 (ISSN-L)
  • 1728-1431
  • 1735-9244
DOI
10.5829/ije.2025.38.07a.07
OpenAlex
W4406918089
Cited by
14
References
0
Citations by year
2026: 7 · 2025: 6 · 2024: 1
FWCI
7.08
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
International Journal of Engineering (publishedVersion, cc-by)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
  • Physical Sciences › Engineering › Mechanical Engineering › Agricultural Engineering and Mechanization
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
Keywords
agricultural robotics, maize production, robots, precision agriculture, weeding robot, harvesting robots, crop monitoring, robot design, technology adoption barriers, sustainable food production

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