Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.0
Journals
AgriEngineering
Special Issues
Advancing Smart Farming through Agricultural Robots and Automation Technologies
share announcement

Advancing Smart Farming through Agricultural Robots and Automation Technologies

A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Agricultural Mechanization and Machinery".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 12113

Special Issue Editor

Dr. Simone Pascuzzi

E-Mail Website
Guest Editor
Department of Soil, Plant and Food Science, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy
Interests: agricultural robotics; unmanned ground vehicles; unmanned aerial vehicles; remote sensing; sensors; agricultural automation; small unmanned aircraft systems (sUAS); agricultural robotics; machine-vision; renewable energies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Agricultural robotics and automation technologies are two rapidly spreading fields that can revolutionize agriculture through the development of robotic and automatic systems to remedy farm labor shortages, improving efficiency, productivity, and safety with a focus on sustainability.

The term agricultural robot indicates robotic machines, including unmanned ground vehicles (UGVs), hybrid-tractors, manipulators, and unmanned aerial vehicles (UAVs), that support farmers or perform autonomously repetitive and labor-intensive agricultural tasks. Nowadays, the categories of these robots are continuously expanding, and their application’s scenarios can vary significantly, from land preparation and seeding, to crop protection and harvesting.

These robots can be equipped with several sensors and cameras for real-time data collection to monitor soil and environmental parameters. This can help farmers in inputs optimization, to reduce costs and environmental impact and for the early detection of pest infections or nutrient deficiencies.

In this Special Issue, original, high-quality research articles and reviews are welcome.

In this Special Issue, we invite authors to publish their research on the development and application of agricultural robots and automation technologies in the agriculture, forestry and livestock sectors.

Research areas include but are not limited to:

  • Development of robotic systems to reduce farming inputs and environmental impact.
  • Employment in agriculture, forestry, and livestock sectors of unmanned aerial vehicles.
  • 3D image reconstruction and object detection from unmanned aerial and ground vehicles.
  • Precision agriculture and smart farming solutions.
  • Application of sustainable technologies for a greener agriculture.
  • Development of hybrid-electric machinery.
  • Employment of advanced sensors in agriculture, forestry, and livestock sectors.
  • Simulations of robotic systems.
  • Implementation of algorithms for vegetation’s indices assessment, as well as for productivity and yield estimation.
  • Analysis of the challenges connected to the employment of these new technologies.

Prof. Dr. Simone Pascuzzi
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 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 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.

Keywords

  • agricultural robotics
  • automation technologies
  • unmanned ground vehicles
  • unmanned aerial vehicles
  • precision agriculture, forestry, livestock
  • sensors
  • smart farming
  • image reconstruction
  • hybrid-electric machinery
  • algorithms
  • simulation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

21 pages, 4198 KiB  
Article
Integrating a Centrifugal Extraction and Pipeline Transportation System to Improve Efficiency in Shrimp Harvesting Management
by Songphon Thoetrattanakiat, Kiattisak Sangpradit and Grianggai Samseemoung
AgriEngineering 2025, 7(5), 128; https://doi.org/10.3390/agriengineering7050128 - 22 Apr 2025
Viewed by 180
Abstract
The integration of a centrifugal extraction and pipeline transportation system to improve efficiency in shrimp harvesting management into closed-pond aquaculture systems represents a significant advancement in aquaculture technology. This study introduces and assesses the efficiency of the shrimp harvester compared to manual harvesting [...] Read more.
The integration of a centrifugal extraction and pipeline transportation system to improve efficiency in shrimp harvesting management into closed-pond aquaculture systems represents a significant advancement in aquaculture technology. This study introduces and assesses the efficiency of the shrimp harvester compared to manual harvesting methods, examining key parameters such as shrimp harvester quality, shrimp harvester loss rates, and shrimp harvester speed. A particularly noteworthy aspect is the innovative transportation of shrimp through a pipeline, which enhances the transformative potential of this technology. Results indicate that the centrifugal shrimp harvester outperforms manual methods, achieving an impressive yield rate of 3338 kg/h with a minimal loss rate of 0.01%; the trend values for harvester capacity ranged from 0.501 to 1.884 tons of shrimp per hour at 240 rpm, 2.391 to 3.081 tons per hour at 270 rpm, and 3.338 to 3.816 tons per hour at 300 rpm. While this technology shows promise for increasing productivity and minimizing shrimp damage, further investigation is needed to evaluate its economic viability, including operational costs and labor expenses. The study highlights the transformative potential of the centrifugal shrimp harvester and emphasizes the need for ongoing research to ensure its practical application in real-world aquaculture settings. Overall, the centrifugal shrimp harvester is poised to revolutionize shrimp harvesting practices, contributing to more sustainable and efficient aquaculture production. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

21 pages, 15400 KiB  
Article
Aerodynamic Optimization and Wind Field Characterization of a Quadrotor Fruit-Picking Drone Based on LBM-LES
by Zhengqi Zhou, Yonghong Tan, Yongda Lin, Zhili Pan, Linhui Wang, Zhizhuang Liu, Yu Yang, Lizhi Chen and Xuxiang Peng
AgriEngineering 2025, 7(4), 100; https://doi.org/10.3390/agriengineering7040100 - 1 Apr 2025
Viewed by 172
Abstract
Picking fruits from tall fruit trees manually is laborious and inefficient. Rotary-wing drones, a low-altitude carrier platform, can enhance the picking efficiency for tall fruit trees when combined with picking robotic arms. However, during the operation of rotary-wing drones, the wind field changes [...] Read more.
Picking fruits from tall fruit trees manually is laborious and inefficient. Rotary-wing drones, a low-altitude carrier platform, can enhance the picking efficiency for tall fruit trees when combined with picking robotic arms. However, during the operation of rotary-wing drones, the wind field changes dramatically, and the center of gravity of the drone shifts at the moment of picking, leading to poor aerodynamic stability and making it difficult to achieve optimized attitude control. To address the aforementioned issues, this paper constructs a drone and wind field testing platform and employs the Lattice Boltzmann Method and Large Eddy Simulation (LBM-LES) algorithm to solve the high-dynamic, rapidly changing airflow field during the transient picking process of the drone. The aerodynamic structure of the drone is optimized by altering the rotor spacing and duct intake ratio of the harvesting drone. The simulation results indicate that the interaction of airflow between the drone’s rotors significantly affects the stability of the aerodynamic structure. When the rotor spacing is 2.8R and the duct ratio is 1.20, the lift coefficient is increased by 11% compared to the original structure. The test results from the drone and wind field experimental platform show that the rise time (tr) of the drone is shortened by 0.3 s, the maximum peak time (tp) is reduced by 0.35 s, and the adjustment time (ts) is accelerated by 0.4 s. This paper, by studying the transient wind field of the harvesting drone, clarifies the randomness of the transient wind field and its complex vortex structures, optimizes the aerodynamic structure of the harvesting drone, and enhances its aerodynamic stability. The research findings can provide a reference for the aerodynamic optimization of other types of drones. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

14 pages, 5845 KiB  
Article
Simulation Analysis of Energy Inputs Required by Agricultural Machines to Perform Field Operations
by Francesco Paciolla, Katarzyna Łyp-Wrońska, Tommaso Quartarella and Simone Pascuzzi
AgriEngineering 2025, 7(1), 7; https://doi.org/10.3390/agriengineering7010007 - 30 Dec 2024
Viewed by 921
Abstract
The evaluation of direct energy inputs and the assessment of the carbon footprint of an agricultural tractor during the execution of an agricultural operation is a complex task. Methodological approaches such as field surveys and life cycle assessments can provide unreliable and non-repeatable [...] Read more.
The evaluation of direct energy inputs and the assessment of the carbon footprint of an agricultural tractor during the execution of an agricultural operation is a complex task. Methodological approaches such as field surveys and life cycle assessments can provide unreliable and non-repeatable results. This study exploits the use of numerical simulation to assess the fuel consumption of two agricultural tractors and their CO2 emissions during the execution of pesticide treatment and milling. The digital models of the Landini REX 4-120 GB and the Fendt 942 Vario were developed, starting from experimental data acquired during field tests in which the power required at the power take-off (PTO) by the respective operating machine was measured. Two custom working cycles, simulating the two agricultural operations, have been defined and simulated. The estimated fuel consumption was 7.8 L∙ha−1 and 23.2 L∙ha−1, respectively, for the Landini REX 4-120 GB during pesticide treatment and for the Fendt 942 Vario during milling. The corresponding direct energy inputs required for the two agricultural operations were equal to 300.3 MJ∙ha−1 and 893.2 MJ∙ha−1, respectively. The estimated carbon footprint was 26.5 kgCO2∙ha−1 and 68.4 kgCO2∙ha−1 for pesticide treatment and for milling, respectively. Moreover, considering the operational efficiency of the systems, an analysis of the available mechanical work supplied by the fuel was conducted. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

17 pages, 3168 KiB  
Article
Development and Evaluation of a Laser System for Autonomous Weeding Robots
by Vitali Czymmek, Jost Völckner and Stephan Hussmann
AgriEngineering 2024, 6(4), 4425-4441; https://doi.org/10.3390/agriengineering6040251 - 22 Nov 2024
Viewed by 2221
Abstract
Manual weed control is becoming increasingly costly, necessitating the development of alternative methods. This work investigates the feasibility of using laser technology for autonomous weed regulation. We developed a system utilizing a laser scanner to target and eliminate weeds, which was first tested [...] Read more.
Manual weed control is becoming increasingly costly, necessitating the development of alternative methods. This work investigates the feasibility of using laser technology for autonomous weed regulation. We developed a system utilizing a laser scanner to target and eliminate weeds, which was first tested using a pilot laser for accuracy and performance. Subsequently, the system was upgraded with a high-power fiber laser. Experimental results demonstrated a high weed destruction accuracy with real-time capabilities. The system achieved efficient weed control with minimal environmental impact, providing a potential alternative for sustainable agriculture. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

27 pages, 33174 KiB  
Article
Automated Windrow Profiling System in Mechanized Peanut Harvesting
by Alexandre Padilha Senni, Mario Luiz Tronco, Emerson Carlos Pedrino and Rouverson Pereira da Silva
AgriEngineering 2024, 6(4), 3511-3537; https://doi.org/10.3390/agriengineering6040200 - 25 Sep 2024
Cited by 1 | Viewed by 1266
Abstract
In peanut cultivation, the fact that the fruits develop underground presents significant challenges for mechanized harvesting, leading to high loss rates, with values that can exceed 30% of the total production. Since the harvest is conducted indirectly in two stages, losses are higher [...] Read more.
In peanut cultivation, the fact that the fruits develop underground presents significant challenges for mechanized harvesting, leading to high loss rates, with values that can exceed 30% of the total production. Since the harvest is conducted indirectly in two stages, losses are higher during the digging/inverter stage than the collection stage. During the digging process, losses account for about 60% to 70% of total losses, and this operation directly influences the losses during the collection stage. Experimental studies in production fields indicate a strong correlation between losses and the height of the windrow formed after the digging/inversion process, with a positive correlation coefficient of 98.4%. In response to this high correlation, this article presents a system for estimating the windrow profile during mechanized peanut harvesting, allowing for the measurement of crucial characteristics such as the height, width and shape of the windrow, among others. The device uses an infrared laser beam projected onto the ground. The laser projection is captured by a camera strategically positioned above the analyzed area, and through advanced image processing techniques using triangulation, it is possible to measure the windrow profile at sampled points during a real experiment under direct sunlight. The technical literature does not mention any system with these specific characteristics utilizing the techniques described in this article. A comparison between the results obtained with the proposed system and those obtained with a manual profilometer showed a root mean square error of only 28 mm. The proposed system demonstrates significantly greater precision and operates without direct contact with the soil, making it suitable for dynamic implementation in a control mesh for a digging/inversion device in mechanized peanut harvesting and, with minimal adaptations, in other crops, such as beans and potatoes. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

24 pages, 22734 KiB  
Article
Optimizing Orchard Planting Efficiency with a GIS-Integrated Autonomous Soil-Drilling Robot
by Osman Eceoğlu and İlker Ünal
AgriEngineering 2024, 6(3), 2870-2890; https://doi.org/10.3390/agriengineering6030166 - 13 Aug 2024
Cited by 1 | Viewed by 1407
Abstract
A typical orchard’s mechanical operation consists of three or four stages: lining and digging for plantation, moving the seedling from nurseries to the farm, moving the seedling to the planting hole, and planting the seedling in the hole. However, the digging of the [...] Read more.
A typical orchard’s mechanical operation consists of three or four stages: lining and digging for plantation, moving the seedling from nurseries to the farm, moving the seedling to the planting hole, and planting the seedling in the hole. However, the digging of the planting hole is the most time-consuming operation. In fruit orchards, the use of robots is increasingly becoming more prevalent to increase operational efficiency. They offer practical and effective services to both industry and people, whether they are assigned to plant trees, reduce the use of chemical fertilizers, or carry heavy loads to relieve staff. Robots can operate for extended periods of time and can be highly adept at repetitive tasks like planting many trees. The present study aims to identify the locations for planting trees in orchards using geographic information systems (GISs), to develop an autonomous drilling machine and use the developed robot to open planting holes. There is no comparable study on autonomous hole planting in the literature in this regard. The agricultural mobile robot is a four=wheeled nonholonomic robot with differential steering and forwarding capability to stable target positions. The designed mobile robot can be used in fully autonomous, partially autonomous, or fully manual modes. The drilling system, which is a y-axis shifter driven by a DC motor with a reducer includes an auger with a 2.1 HP gasoline engine. SOLIDWORKS 2020 software was used for designing and drawing the mobile robot and drilling system. The Microsoft Visual Basic.NET programming language was used to create the robot navigation system and drilling mechanism software. The cross-track error (XTE), which determines the distances between the actual and desired holes positions, was utilized to analyze the steering accuracy of the mobile robot to the drilling spots. Consequently, the average of the arithmetic means was determined to be 4.35 cm, and the standard deviation was 1.73 cm. This figure indicates that the suggested system is effective for drilling plant holes in orchards. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

Review

Jump to: Research

18 pages, 3201 KiB  
Review
Recent Advances in Agricultural Robots for Automated Weeding
by Chris Lytridis and Theodore Pachidis
AgriEngineering 2024, 6(3), 3279-3296; https://doi.org/10.3390/agriengineering6030187 - 11 Sep 2024
Cited by 2 | Viewed by 4989
Abstract
Weeds are one of the primary concerns in agriculture since they compete with crops for nutrients and water, and they also attract insects and pests and are, therefore, hindering crop yield. Moreover, seasonal labour shortages necessitate the automation of such agricultural tasks using [...] Read more.
Weeds are one of the primary concerns in agriculture since they compete with crops for nutrients and water, and they also attract insects and pests and are, therefore, hindering crop yield. Moreover, seasonal labour shortages necessitate the automation of such agricultural tasks using machines. For this reason, advances in agricultural robotics have led to many attempts to produce autonomous machines that aim to address the task of weeding both effectively and efficiently. Some of these machines are implementing chemical-based weeding methods using herbicides. The challenge for these machines is the targeted delivery of the herbicide so that the environmental impact of the chemical is minimised. However, environmental concerns drive weeding robots away from herbicide use and increasingly utilise mechanical weeding tools or even laser-based devices. In this case, the challenge is the development and application of effective tools. This paper reviews the progress made in the field of weeding robots during the last decade. Trends during this period are identified, and the current state-of-the-art works are highlighted. Finally, the paper examines the areas where the current technological solutions are still lacking, and recommendations on future directions are made. Full article
(This article belongs to the Special Issue Advancing Smart Farming through Agricultural Robots and Automation Technologies)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop