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A Comprehensive Review of Path Planning for Agricultural Ground Robots

Author

Listed:
  • Suprava Chakraborty

    (TIFAC-CORE, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India)

  • Devaraj Elangovan

    (TIFAC-CORE, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India)

  • Padma Lakshmi Govindarajan

    (Vellore Institute of Technology (VIT), School of Agricultural Innovations and Advanced Learning, Vellore 632014, Tamil Nadu, India)

  • Mohamed F. ELnaggar

    (Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 16273, Saudi Arabia
    Department of Electrical Power and Machines Engineering, Faculty of Engineering, Helwan University, Helwan 11795, Egypt)

  • Mohammed M. Alrashed

    (Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 16273, Saudi Arabia)

  • Salah Kamel

    (Department of Electrical Engineering, Aswan University, Aswan 81542, Egypt)

Abstract

The population of the world is predicted to reach nine billion by 2050, implying that agricultural output must continue to rise. To deal with population expansion, agricultural chores must be mechanized and automated. Over the last decade, ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. This research examines several agricultural applications as well as the path planning approach used. The purpose of this study is to investigate the current literature on path/trajectory planning aspects of ground robots in agriculture using a systematic literature review technique, to contribute to the goal of contributing new information in the field. Coverage route planning appears to be less advanced in agriculture than point-to-point path routing, according to the finding, which is due to the fact that covering activities are usually required for agricultural applications, but precision agriculture necessitates point-to-point navigation. In the recent era, precision agriculture is getting more attention. The conclusion presented here demonstrates that both field coverage and point-to-point navigation have been applied successfully in path planning for agricultural robots.

Suggested Citation

  • Suprava Chakraborty & Devaraj Elangovan & Padma Lakshmi Govindarajan & Mohamed F. ELnaggar & Mohammed M. Alrashed & Salah Kamel, 2022. "A Comprehensive Review of Path Planning for Agricultural Ground Robots," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9156-:d:872006
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    References listed on IDEAS

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    2. Cristiano Fragassa & Giuliano Vitali & Luis Emmi & Marco Arru, 2023. "A New Procedure for Combining UAV-Based Imagery and Machine Learning in Precision Agriculture," Sustainability, MDPI, vol. 15(2), pages 1-25, January.
    3. Tyler Parsons & Fattah Hanafi Sheikhha & Omid Ahmadi Khiyavi & Jaho Seo & Wongun Kim & Sangdae Lee, 2022. "Optimal Path Generation with Obstacle Avoidance and Subfield Connection for an Autonomous Tractor," Agriculture, MDPI, vol. 13(1), pages 1-16, December.
    4. Alexander V. Klokov & Egor Yu. Loktionov & Yuri V. Loktionov & Vladimir A. Panchenko & Elizaveta S. Sharaborova, 2023. "A Mini-Review of Current Activities and Future Trends in Agrivoltaics," Energies, MDPI, vol. 16(7), pages 1-18, March.

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