Unmanned Ground Vehicles in Precision Farming Services: An Integrated Emulation Modelling Approach

  • Dimitrios BechtsisEmail author
  • Vasileios Moisiadis
  • Naoum Tsolakis
  • Dimitrios Vlachos
  • Dionysis Bochtis
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 953)


Autonomous systems are a promising alternative for safely executing precision farming activities in a 24/7 perspective. In this context Unmanned Ground Vehicles (UGVs) are used in custom agricultural fields, with sophisticated sensors and data fusion techniques for real-time mapping and navigation. The aim of this study is to present a simulation software tool for providing effective and efficient farming activities in orchard fields and demonstrating the applicability of simulation in routing algorithms, hence increasing productivity, while dynamically addressing operational and tactical level uncertainties. The three dimensional virtual world includes the field layout and the static objects (orchard trees, obstacles, physical boundaries) and is constructed in the open source Gazebo simulation software while the Robot Operating System (ROS) and the implemented algorithms are tested using a custom vehicle. As a result a routing algorithm is executed and enables the UGV to pass through all the orchard trees while dynamically avoiding static and dynamic obstacles. Unlike existing sophisticated tools, the developed mechanism could accommodate an extensive variety of agricultural activities and could be transparently transferred from the simulation environment to real world ROS compatible UGVs providing user-friendly and highly customizable navigation.


Precision farming Robot Operating System UGV simulation Real-time navigation Orchard field 



The work was supported by the project “Research Synergy to address major challenges in the nexus: energy-environment-agricultural production (Food, Water, Materials)” - NEXUS, funded by the Greek Secretariat for Research and Technology (GSRT) – Pr. No. MIS 5002496.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Automation EngineeringAlexander Technological Educational Institute of ThessalonikiThessalonikiGreece
  2. 2.Institute for Bio-Economy and Agri-Technology (IBO)Centre for Research and Technology Hellas (CERTH)ThessalonikiGreece
  3. 3.Centre for International Manufacturing, Institute for Manufacturing, Department of Engineering, School of TechnologyUniversity of CambridgeCambridgeUK
  4. 4.Department of Mechanical EngineeringAristotle University of ThessalonikiThessalonikiGreece

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