Deep Learning Applications in Agricultural Robotics and Automation
A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Computer Applications and Artificial Intelligence in Agriculture".
Deadline for manuscript submissions: 30 June 2027 | Viewed by 121
Editors
Interests: smart farming; precision agriculture; precision livestock farming; agricultural informatics; deep learning; computer vision; agricultural robotics
Interests: machine learning systems; deep learning systems; artificial intelligence; autonomous agricultural machinery; precision agriculture; remote sensing technologies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, rapid advancements in artificial intelligence (AI) have created significant opportunities for the automation of agricultural machinery, the deployment of agricultural robotics, and the integration of intelligent data-driven farm management systems. Deep learning, widely recognized as the driving force behind modern AI advances, lies at the technological nucleus of ongoing efforts to develop the current generation of smart systems with robotics capable of delivery adaptive autonomy, real-time perception, and autonomous decision-making.
Moreover, deep learning is reshaping how agricultural technologies are developed and deployed. Advances in data-driven frameworks accelerate research and innovation through rapid prototyping, iterative model refinement, and streamlined deployment of intelligent systems. The integration of deep learning-based tools, including large language models (LLMs), further enhances this process by enabling fast design, implementation, and optimization of end-to-end pipelines. This synergy allows researchers and practitioners to translate concepts into functional solutions, particularly in computer vision, field robotics, and information systems. Such acceleration is essential in contemporary agriculture, where delayed innovation directly impacts productivity, resilience, and economic viability.
In response to these opportunities and challenges, this Special Issue invites contributions that advance and showcase recent developments in deep learning applications for agricultural systems, robotics, and automation, including, but not limited to, edge intelligence, digital twins, multisensory integration, cloud–edge computing, computer vision, and autonomous navigation. We welcome both methodological innovations and application-driven studies that enable the deployment of smart, resilient, and scalable farming systems.
Topics of interest include (but are not limited to):
- Deep learning for precision agriculture;
- Crop monitoring and phenotyping;
- Multimodal deep learning and sensor fusion;
- Autonomous agricultural robotics and adaptive autonomy;
- Edge intelligence for real-time farming systems;
- Sim-to-real transfer in agricultural robotics;
- Computer vision for agricultural inspection and analysis;
- Digital twins and cyber–physical agricultural systems;
- Deep learning model optimization and performance improvement.
Dr. Victor Massaki Nakaguchi
Dr. Ahamed Tofael
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- smart farming
- agricultural robotics
- agricultural information engineering
- precision farming
- AI-driven systems
- smart farming technology
- agricultural automation
- agricultural machinery
- autonomous tractor
- robotic harvester
- path planning
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