Application of Mechatronics in Agriculture

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: 10 May 2024 | Viewed by 1670

Special Issue Editors

Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58108, USA
Interests: machine learning applications; machine vision; image processing; mechatronics; control; autonomous systems; MEMS
Special Issues, Collections and Topics in MDPI journals
1. Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy
2. PIC4SeR Centre Coordinator, 10141 Torino, Italy
Interests: autonomous vehicles; drones; embedded systems; precision agriculture; search and rescue; service robotics; simultaneous localization and mapping; smart cities

Special Issue Information

Dear Colleagues,

Various UN statistical projects envisage that the population of the world will probably reach 9.7 billion by 2050, and about 70% of the population will live in cities. This is a prevalent trend in many developed and developing countries; workforce shortages already exist concerning the increase in agricultural production to meet these demands. The energy costs and environmental concerns of agricultural production have become prominent factors due to alarming levels of greenhouse gas (GHG) emissions and increasing fossil fuel costs. All these concerns require extensive use of precision agriculture and automation to increase yield. Robots and autonomous machines can address these pressing issues and assist farmers in resolving the labor shortage and the need for increased crop yield. The applications of mechatronic systems and autonomous machines have permeated many domains of agriculture, such as driver assistance systems for harvesting, variable rate technology (VRT)-based fertilizers, sprayers, etc. Autonomously operating machines help meet labor shortages and enhance agricultural productivity, the sustainability of economic development, and the growth of farms.

Due to their accuracy and energy efficiency, autonomously operating unmanned machines can significantly increase quality and quantity in agricultural production. Moreover, they can help curtail GHG emissions and the negative effects of fertilizers by using enhanced VRT-based fertilizer application and watering systems. Another mainstream research paradigm is the application of cloud-based data sharing and Edge AI for data processing.

Several potentially challenging issues exist in developing and implementing autonomously driven unmanned vehicles, including varying terrain conditions, soil and visibility changes due to weather conditions, and significantly varying farm fields. Sensing the surrounding environment and controlling systems in the face of these uncertainties pose significant challenges to using autonomously driven vehicles.

The scientific/engineering challenges mentioned above concerning developing and applying mechatronic systems and robots in autonomously driven unmanned machines for agriculture are anticipated to be the topics of research and review papers in this Special Issue. This Special Issue aims to discover, elaborate, and share the different scientific studies and development methodologies addressing challenges in employing autonomously operating machines and systems applying mechatronic system development principles to enhance agricultural production. We invite all researchers to submit their findings in the study of mechatronics in agriculture.

Dr. Sulaymon Eshkabilov
Dr. Marcello Chiaberge
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 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. Agriculture 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 2600 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

  • mechatronics in agriculture
  • robotics
  • automation
  • sensors
  • Wi-Fi communication
  • remote sensing
  • autonomous control
  • machine vision
  • novel robotic platforms
  • artificial intelligence
  • traction systems for agriculture
  • emission reduction
  • energy optimization

Published Papers (1 paper)

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Review

42 pages, 15702 KiB  
Review
A Comprehensive Overview of Control Algorithms, Sensors, Actuators, and Communication Tools of Autonomous All-Terrain Vehicles in Agriculture
by Hamed Etezadi and Sulaymon Eshkabilov
Agriculture 2024, 14(2), 163; https://doi.org/10.3390/agriculture14020163 - 23 Jan 2024
Viewed by 1176
Abstract
This review paper discusses the development trends of agricultural autonomous all-terrain vehicles (AATVs) from four cornerstones, such as (1) control strategy and algorithms, (2) sensors, (3) data communication tools and systems, and (4) controllers and actuators, based on 221 papers published in peer-reviewed [...] Read more.
This review paper discusses the development trends of agricultural autonomous all-terrain vehicles (AATVs) from four cornerstones, such as (1) control strategy and algorithms, (2) sensors, (3) data communication tools and systems, and (4) controllers and actuators, based on 221 papers published in peer-reviewed journals for 1960–2023. The paper highlights a comparative analysis of commonly employed control methods and algorithms by highlighting their advantages and disadvantages. It gives comparative analyses of sensors, data communication tools, actuators, and hardware-embedded controllers. In recent years, many novel developments in AATVs have been made due to advancements in wireless and remote communication, high-speed data processors, sensors, computer vision, and broader applications of AI tools. Technical advancements in fully autonomous control of AATVs remain limited, requiring research into accurate estimation of terrain mechanics, identifying uncertainties, and making fast and accurate decisions, as well as utilizing wireless communication and edge cloud computing. Furthermore, most of the developments are at the research level and have many practical limitations due to terrain and weather conditions. Full article
(This article belongs to the Special Issue Application of Mechatronics in Agriculture)
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