Applications of Robotics/UAVs and Computer Vision in Agricultural Engineering
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: 31 January 2027 | Viewed by 277
Special Issue Editors
Interests: robotics; route planning; precision agriculture; machine learning; optimization; simulation
Interests: operations research; route planning; logistics; supply chain management; system engineering; precision agriculture
Special Issues, Collections and Topics in MDPI journals
Interests: precision and digital farming; vineyard spatial variability monitoring; proximal and remote sensing; agricultural engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing integration of robotics/unmanned aerial vehicles (UAVs) and computer vision technologies is reshaping the landscape of modern agricultural engineering. These innovations are driving the transition toward intelligent, data-driven, and sustainable farming systems capable of addressing global challenges such as labor shortages, environmental sustainability, and food security. Robotics and UAVs equipped with advanced sensors and vision-based algorithms enable precise field operations, continuous crop monitoring, and real-time decision-making. This Special Issue aims to highlight cutting-edge research and practical advancements that explore how these technologies contribute to improving efficiency, productivity, and sustainability across all stages of agricultural production.
Research Areas
This Special Issue welcomes original research articles, reviews, and technical papers focusing on (but not limited to) the following areas:
- Autonomous Agricultural Robots and UAVs.
- Computer Vision and Artificial Intelligence in Agriculture.
- UAV-Based Remote Sensing and Mapping.
- Coverage Path Planning and Cooperative Navigation.
- Multi-Sensor Fusion and Perception Systems.
- Automation of Agricultural Operations.
- AI-Driven Decision Support Systems.
- Simulation and Digital Twin Technologies.
- Sustainability, Safety, and Environmental Assessment.
Dr. Mahdi Vahdanjoo
Prof. Dr. Claus Grøn Sørensen
Dr. Massimo Ferro
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-blind 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
- agricultural robotics
- unmanned aerial vehicles (UAVS)
- precision agriculture
- computer vision
- artificial intelligence (AI)
- machine/deep learning
- field automation
- autonomous navigation
- coverage path planning
- sensor fusion
- remote sensing
- crop monitoring
- digital twin
- smart farming
- decision support systems
- sustainable agriculture
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