Robotic Tractors

Dear Colleagues,

In the last few decades, precise management of agricultural and farming land has been made possible thanks to the development of new technologies, including industry 4.0, global positioning systems (GPS), geographic information systems (GIS), sensors, automation of agricultural machinery and high-resolution image sensing. As a result, the concepts of precision agriculture, agriculture 4.0, digital agriculture and smart farming have emerged as management strategies that use information technologies to collect and process data from multiple sources in order to facilitate the control and decision-making associated with farming and agricultural production. This is especially interesting in organic farming tasks in which the treatments are more expensive and the possibilities are more limited.

This Special Issue is focused on research works about the design, development, improvement and testing of robotic tractors and other types of automatic and robotic systems for any agricultural or farming task. It is aimed at gathering recent developments related to the use of robots and automation in agriculture.  Contributions could include, but are not limited to, the following areas:

• Design, development or testing of robotic tractors, both autonomous and collaborative, or any type of agricultural robot. Currently, we can find research on fleets of robots, which will collapse between them, and other collaborative robots that work hand in hand with people.
• The new generation of automatic and robotic systems in precision agriculture.
• The effects of agricultural robots on the enviroment and their role in organic agriculture.
• Use of computer vision, artificial intelligence, 3D point cloud analysis, digital elevation models (DEM) and decision support tools in the control systems for agriculture tasks.
• Agriculture 4.0, smart farming, digital agriculture and the role of industry 4.0 in agriculture and livestock farming.
• Location systems and path tracking in agricultural robots.
• Optimization of task resources using robotics: precision seeding, path planning, reduction of herbicide, pesticide and fertilizer use, etc.
• Power systems in agricultural robots: hybrid power, energy efficiency; optimization of fuel consumption.

Dr. Mariano Gonzalez-de-Soto
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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 quarterly 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 1600 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.

• Robotic tractors
• Autonomous robots
• Collaborative robots
• Power systems
• Precision agriculture
• Computer vision
• Agriculture 4.0
• Robots in organic farming
• Decision support tools
• Location systems, smart farming, fleets of robots
• herbicide saving
• weed control
• pest control
• autonomous seeders
• hybrid power
• energy efficiency
• fuel consumption
• path planning
• agriculture emissions
• digital elevation model (DEM)
• digital agriculture
• industry 4.0 in agriculture
• industry 4.0 in farming
• smart farming
• artificial intelligence
• 3D point cloud analysis