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Robotics
Special Issues
Smart Agriculture with AI and Robotics
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Smart Agriculture with AI and Robotics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Agricultural and Field Robotics".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 1710

Special Issue Editor

Dr. Antonio Valente

E-Mail Website
Guest Editor
1. School of Sciences and Technology-Engineering Department (UTAD), 5000-801 Vila Real, Portugal
2. INESC TEC, Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
Interests: educational robotics; robotic competitions; robotics for agriculture; IoT; sensors; sensors for agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of robotics and artificial intelligence (AI) into agriculture is revolutionizing the way we grow, manage, and harvest food. This Special Issue focuses on cutting-edge advances in intelligent robotic systems designed for smart agriculture, with emphasis on autonomy, precision, and sustainability. Topics of interest include agricultural mobile robots and drones, AI-driven perception and decision-making, task planning for field operations, crop monitoring and yield estimation, and human–robot collaboration in unstructured environments. Particular focus is given to real-world deployment of robotic solutions that address agricultural challenges such as labor shortages, resource efficiency, and climate adaptation. We welcome original research articles, reviews, and case studies that demonstrate the potential of robotics and AI in transforming agriculture into a more productive, data-driven, and environmentally sustainable sector.

Dr. Antonio Valente
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. Robotics 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
  • AI for precision farming
  • autonomous field robots
  • machine vision for crops
  • human–robot collaboration
  • UAVs in agriculture
  • smart sensing and perception
  • path planning in unstructured terrain
  • sustainable farming automation
  • learning-based control systems

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Published Papers (2 papers)

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Research

20 pages, 3007 KB  
Article
Co-Simulation Model of an Autonomous Driving Rover for Agricultural Applications
by Salvatore Martelli, Valerio Martini, Francesco Mocera and Aurelio Soma’
Robotics 2025, 14(9), 120; https://doi.org/10.3390/robotics14090120 - 29 Aug 2025
Viewed by 693
Abstract
The implementation of autonomous rovers in agriculture could be a promising solution to ensure, at the same time, productivity and sustainability. One of the key points of this kind of vehicle concerns their autonomous driving strategy. Generally, the strategy should include the path [...] Read more.
The implementation of autonomous rovers in agriculture could be a promising solution to ensure, at the same time, productivity and sustainability. One of the key points of this kind of vehicle concerns their autonomous driving strategy. Generally, the strategy should include the path planning and path following algorithms. In this paper, an autonomous driving strategy assessing both is presented. To evaluate the effectiveness of this strategy, a case study of an agricultural rover is presented. A co-simulation model, including a multibody model of the rover, is developed in Matlab/Simulink R2021b and Hexagon Adams 2024 environments to virtually test the rover capabilities and the effects of its dynamics on the robustness of the algorithm. Given different orchard configurations, common but critical work scenarios are investigated, namely a 180° turn and an obstacle avoidance manoeuvre. The actual trajectory obtained during simulations are compared to the ideal trajectory defined in the path planning stage. Furthermore, the torque demand at the electric motors is evaluated. To consider a wide range of possible operating conditions, additional tests with different terrains, payloads and road slopes are included. Results showed that the rover managed to accomplish the considered manoeuvres on loam soil with a maximum trajectory deviation of 0.58 m, but a temporary overload of the motors is needed. On the contrary, in case of difficult terrains, such as muddy soil, the rover was not able to perform the manoeuvre. To limit tire slip, a traction control algorithm is developed and implemented, and the results are compared with the case without control. Full article
(This article belongs to the Special Issue Smart Agriculture with AI and Robotics)
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24 pages, 4130 KB  
Article
Experimental Comparative Analysis of Centralized vs. Decentralized Coordination of Aerial–Ground Robotic Teams for Agricultural Operations
by Dimitris Katikaridis, Lefteris Benos, Patrizia Busato, Dimitrios Kateris, Elpiniki Papageorgiou, George Karras and Dionysis Bochtis
Robotics 2025, 14(9), 119; https://doi.org/10.3390/robotics14090119 - 28 Aug 2025
Viewed by 759
Abstract
Reliable and fast communication between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) is essential for effective coordination in agricultural settings, particularly when human involvement is part of the system. This study systematically compares two communication architectures representing centralized and decentralized communication [...] Read more.
Reliable and fast communication between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) is essential for effective coordination in agricultural settings, particularly when human involvement is part of the system. This study systematically compares two communication architectures representing centralized and decentralized communication frameworks: (a) MAVLink (decentralized) and (b) Farm Management Information System (FMIS) (centralized). Field experiments were conducted in both empty field and orchard environments, using a rotary UAV for worker detection and a UGV responding to intent signaled through color-coded hats. Across 120 trials, the system performance was assessed in terms of communication reliability, latency, energy consumption, and responsiveness. FMIS consistently demonstrated higher message delivery success rates (97% in both environments) than MAVLink (83% in the empty field and 70% in the orchard). However, it resulted in higher UGV resource usage. Conversely, MAVLink achieved reduced UGV power draw and lower latency, but it was more affected by obstructed settings and also resulted in increased UAV battery consumption. In conclusion, MAVLink is suitable for time-sensitive operations that require rapid feedback, while FMIS is better suited for tasks that demand reliable communication in complex agricultural environments. Consequently, the selection between MAVLink and FMIS should be guided by the specific mission goals and environmental conditions. Full article
(This article belongs to the Special Issue Smart Agriculture with AI and Robotics)
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