IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i2p163-d1324325.html
   My bibliography  Save this article

A Comprehensive Overview of Control Algorithms, Sensors, Actuators, and Communication Tools of Autonomous All-Terrain Vehicles in Agriculture

Author

Listed:
  • Hamed Etezadi

    (Department of Bioresource Engineering, McGill University, Montréal, QC H9X 3V9, Canada)

  • Sulaymon Eshkabilov

    (Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58102, USA)

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 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.

Suggested Citation

  • Hamed Etezadi & Sulaymon Eshkabilov, 2024. "A Comprehensive Overview of Control Algorithms, Sensors, Actuators, and Communication Tools of Autonomous All-Terrain Vehicles in Agriculture," Agriculture, MDPI, vol. 14(2), pages 1-42, January.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:2:p:163-:d:1324325
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/2/163/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/2/163/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2018. "Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps," Energies, MDPI, vol. 11(3), pages 1-41, February.
    2. En Lu & Jialin Xue & Tiaotiao Chen & Song Jiang, 2023. "Robust Trajectory Tracking Control of an Autonomous Tractor-Trailer Considering Model Parameter Uncertainties and Disturbances," Agriculture, MDPI, vol. 13(4), pages 1-17, April.
    3. Chen Jie & Guo Yanling, 2021. "Research on Control Strategy of the Electric Power Steering System for All-Terrain Vehicles Based on Model Predictive Current Control," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-15, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    2. Anass Berouine & Radouane Ouladsine & Mohamed Bakhouya & Mohamed Essaaidi, 2020. "Towards a Real-Time Predictive Management Approach of Indoor Air Quality in Energy-Efficient Buildings," Energies, MDPI, vol. 13(12), pages 1-16, June.
    3. Rafiq Asghar & Francesco Riganti Fulginei & Hamid Wadood & Sarmad Saeed, 2023. "A Review of Load Frequency Control Schemes Deployed for Wind-Integrated Power Systems," Sustainability, MDPI, vol. 15(10), pages 1-29, May.
    4. Anh Tuan Phan & Thi Tuyet Hong Vu & Dinh Quang Nguyen & Eleonora Riva Sanseverino & Hang Thi-Thuy Le & Van Cong Bui, 2022. "Data Compensation with Gaussian Processes Regression: Application in Smart Building’s Sensor Network," Energies, MDPI, vol. 15(23), pages 1-16, December.
    5. Tayyaba Nosheen & Ahsan Ali & Muhammad Umar Chaudhry & Dmitry Nazarenko & Inam ul Hasan Shaikh & Vadim Bolshev & Muhammad Munwar Iqbal & Sohail Khalid & Vladimir Panchenko, 2023. "A Fractional Order Controller for Sensorless Speed Control of an Induction Motor," Energies, MDPI, vol. 16(4), pages 1-15, February.
    6. Serafín Alonso & Antonio Morán & Miguel Ángel Prada & Perfecto Reguera & Juan José Fuertes & Manuel Domínguez, 2019. "A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study," Energies, MDPI, vol. 12(5), pages 1-28, March.
    7. Phummarin Thavitchasri & Dechrit Maneetham & Padma Nyoman Crisnapati, 2024. "Intelligent Surface Recognition for Autonomous Tractors Using Ensemble Learning with BNO055 IMU Sensor Data," Agriculture, MDPI, vol. 14(9), pages 1-21, September.
    8. Jiapeng Yan & Huifang Kong & Zhihong Man, 2022. "Recurrent Neural Network-Based Nonlinear Optimization for Braking Control of Electric Vehicles," Energies, MDPI, vol. 15(24), pages 1-17, December.
    9. Moudgil, Vipul & Hewage, Kasun & Hussain, Syed Asad & Sadiq, Rehan, 2023. "Integration of IoT in building energy infrastructure: A critical review on challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    10. Halhoul Merabet, Ghezlane & Essaaidi, Mohamed & Ben Haddou, Mohamed & Qolomany, Basheer & Qadir, Junaid & Anan, Muhammad & Al-Fuqaha, Ala & Abid, Mohamed Riduan & Benhaddou, Driss, 2021. "Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    11. Amal Azzi & Mohamed Tabaa & Badr Chegari & Hanaa Hachimi, 2024. "Balancing Sustainability and Comfort: A Holistic Study of Building Control Strategies That Meet the Global Standards for Efficiency and Thermal Comfort," Sustainability, MDPI, vol. 16(5), pages 1-36, March.
    12. Polash Banerjee, 2022. "MODIS-FIRMS and ground-truthing-based wildfire likelihood mapping of Sikkim Himalaya using machine learning algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 899-935, January.
    13. Ahmad Esmaeilzadeh & Brian Deal & Aghil Yousefi-Koma & Mohammad Reza Zakerzadeh, 2022. "How Multi-Criterion Optimized Control Methods Improve Effectiveness of Multi-Zone Building Heating System Upgrading," Energies, MDPI, vol. 15(22), pages 1-27, November.
    14. Zhang, Menghang & Yan, Tingxiang & Wang, Wei & Jia, Xuexiu & Wang, Jin & Klemeš, Jiří Jaromír, 2022. "Energy-saving design and control strategy towards modern sustainable greenhouse: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    15. Iddio, E. & Wang, L. & Thomas, Y. & McMorrow, G. & Denzer, A., 2020. "Energy efficient operation and modeling for greenhouses: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    16. Alberto Garces-Jimenez & Jose-Manuel Gomez-Pulido & Nuria Gallego-Salvador & Alvaro-Jose Garcia-Tejedor, 2021. "Genetic and Swarm Algorithms for Optimizing the Control of Building HVAC Systems Using Real Data: A Comparative Study," Mathematics, MDPI, vol. 9(18), pages 1-24, September.
    17. Michał Markiewicz & Aleksander Skała & Jakub Grela & Szymon Janusz & Tadeusz Stasiak & Dominik Latoń & Andrzej Bielecki & Katarzyna Bańczyk, 2023. "The Architecture for Testing Central Heating Control Algorithms with Feedback from Wireless Temperature Sensors," Energies, MDPI, vol. 16(14), pages 1-15, July.
    18. Mesfer Al Duhayyim & Heba G. Mohamed & Jaber S. Alzahrani & Rana Alabdan & Mohamed Mousa & Abu Sarwar Zamani & Ishfaq Yaseen & Mohamed Ibrahim Alsaid, 2022. "Modeling of Fuzzy Cognitive Maps with a Metaheuristics-Based Rainfall Prediction System," Sustainability, MDPI, vol. 15(1), pages 1-16, December.
    19. David Marcos-Andrade & Francisco Beltran-Carbajal & Ivan Rivas-Cambero & Hugo Yañez-Badillo & Antonio Favela-Contreras & Julio C. Rosas-Caro, 2024. "Sliding Mode Speed Control in Synchronous Motors for Agriculture Machinery: A Chattering Suppression Approach," Agriculture, MDPI, vol. 14(5), pages 1-25, May.
    20. Ivan Grcić & Hrvoje Pandžić & Damir Novosel, 2021. "Fault Detection in DC Microgrids Using Short-Time Fourier Transform," Energies, MDPI, vol. 14(2), pages 1-14, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:2:p:163-:d:1324325. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.