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Exploiting the Internet Resources for Autonomous Robots in Agriculture

Author

Listed:
  • Luis Emmi

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

  • Roemi Fernández

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

  • Pablo Gonzalez-de-Santos

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

  • Matteo Francia

    (Department of Computer Science and Engineering (DISI), Alma Mater Studiorum-University of Bologna, 40127 Bologna, Italy)

  • Matteo Golfarelli

    (Department of Computer Science and Engineering (DISI), Alma Mater Studiorum-University of Bologna, 40127 Bologna, Italy)

  • Giuliano Vitali

    (Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum-University of Bologna, 40127 Bologna, Italy)

  • Hendrik Sandmann

    (Laser Zentrum Hannover e.V., Hollerithallee 8, 30419 Hannover, Germany)

  • Michael Hustedt

    (Laser Zentrum Hannover e.V., Hollerithallee 8, 30419 Hannover, Germany)

  • Merve Wollweber

    (Laser Zentrum Hannover e.V., Hollerithallee 8, 30419 Hannover, Germany)

Abstract

Autonomous robots in the agri-food sector are increasing yearly, promoting the application of precision agriculture techniques. The same applies to online services and techniques implemented over the Internet, such as the Internet of Things (IoT) and cloud computing, which make big data, edge computing, and digital twins technologies possible. Developers of autonomous vehicles understand that autonomous robots for agriculture must take advantage of these techniques on the Internet to strengthen their usability. This integration can be achieved using different strategies, but existing tools can facilitate integration by providing benefits for developers and users. This study presents an architecture to integrate the different components of an autonomous robot that provides access to the cloud, taking advantage of the services provided regarding data storage, scalability, accessibility, data sharing, and data analytics. In addition, the study reveals the advantages of integrating new technologies into autonomous robots that can bring significant benefits to farmers. The architecture is based on the Robot Operating System (ROS), a collection of software applications for communication among subsystems, and FIWARE (Future Internet WARE), a framework of open-source components that accelerates the development of intelligent solutions. To validate and assess the proposed architecture, this study focuses on a specific example of an innovative weeding application with laser technology in agriculture. The robot controller is distributed into the robot hardware, which provides real-time functions, and the cloud, which provides access to online resources. Analyzing the resulting characteristics, such as transfer speed, latency, response and processing time, and response status based on requests, enabled positive assessment of the use of ROS and FIWARE for integrating autonomous robots and the Internet.

Suggested Citation

  • Luis Emmi & Roemi Fernández & Pablo Gonzalez-de-Santos & Matteo Francia & Matteo Golfarelli & Giuliano Vitali & Hendrik Sandmann & Michael Hustedt & Merve Wollweber, 2023. "Exploiting the Internet Resources for Autonomous Robots in Agriculture," Agriculture, MDPI, vol. 13(5), pages 1-22, May.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:5:p:1005-:d:1138185
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    References listed on IDEAS

    as
    1. López-Riquelme, J.A. & Pavón-Pulido, N. & Navarro-Hellín, H. & Soto-Valles, F. & Torres-Sánchez, R., 2017. "A software architecture based on FIWARE cloud for Precision Agriculture," Agricultural Water Management, Elsevier, vol. 183(C), pages 123-135.
    2. Dongxiao Yang & Didong Li & Huafei Sun, 2013. "2D Dubins Path in Environments with Obstacle," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-6, November.
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    Citations

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    Cited by:

    1. Beata Michaliszyn-Gabryś & Joachim Bronder & Wanda Jarosz & Janusz Krupanek, 2024. "Potential of Eco-Weeding with High-Power Laser Adoption from the Farmers’ Perspective," Sustainability, MDPI, vol. 16(6), pages 1-26, March.
    2. Jiazheng Shen & Tang Sai Hong & Luxin Fan & Ruixin Zhao & Mohd Khairol Anuar b. Mohd Ariffin & Azizan bin As’arry, 2024. "Development of an Improved GWO Algorithm for Solving Optimal Paths in Complex Vertical Farms with Multi-Robot Multi-Tasking," Agriculture, MDPI, vol. 14(8), pages 1-26, August.
    3. Ruth Cordova-Cardenas & Luis Emmi & Pablo Gonzalez-de-Santos, 2023. "Enabling Autonomous Navigation on the Farm: A Mission Planner for Agricultural Tasks," Agriculture, MDPI, vol. 13(12), pages 1-19, November.
    4. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

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