Agro Intelligence

Robotics / AI / Informatics

The Domain’s primary research areas focus on Robotics, Informatics and Artificial Intelligence application in bio-production systems.

Our Vision

Our vision includes the integration of all the technological advances in agriculture and other applicable domains, towards digitising and automatising the production systems leading to a more sustainable and environmentally safe agriculture. Therefore iBO follows a multidisciplinary approach in the development of an ecosystem that will lead to the farming of the future.


Unmanned Aerial Vehicle performing low-flight-altitude field scouting

Light-weight UGVs

Small ground robotic platforms performing autonomous targeted site-specific sensing operations

Medium-weight UGVs

Ground robotic platforms performing autonomous field preparation and sensing operations


Sensing systems mapping properties within the greenhouse environment


Wireless sensor network recording plant, soil and environmental parameters on regular basis


Fixed wing Unmanned Aerial Vehicle recording field variability

Research Applications

Farm Management Information Systems

iBO is developing, across various research projects, a series of Farm Management Information Systems- (FMIS) and Agricultural Management dedicated Decision Support Systems (DSS), aiming at transforming agricultural production to a fully controlled and monitored system. Development of algorithmic optimization applications is one of the key research niches in iBO.

The systems are based on a well-designed cloud architecture, which provides an out of the box ability to scale drastically on demand. In addition, the abundance of cloud storage and computational speed facilitates the use of containerization techniques to host multiple well-orchestrated micro-services and  the ease of intercommunication with other devices or services across the cloud.


Mobile Robotics

iBO is a key player in the area of agricultural robotics and performs intensive studies in the synergy of unmanned aerial and ground vehicles (UAVs-UGVs), and their interaction with humans within open air (arable farming, orchard farming, horticulture) and controlled (greenhouse) agricultural environments. Main focus is given at:

  • Outdoor awareness and navigation
  • High Level control (Mission planning, Route planning, Task planning)
  • ROS-based development
  • Autonomous data acquisition
Raw Image
Detection Layer

Machine Learning

Machine learning applications are particularly useful in solving problems in agriculture. Nowadays, with the unprecedented use of IoT and Cloud Computing, we can train models with a huge variety of data from multiple sources and discover patterns that we were unable to find in the past, due to lack of storage and computational speed. In our institute we perform extensive studies using classification, clustering  algorithms and Artificial Neural Networks in the areas of:

  • Weed Detection
  • Yield prediction
  • Weather forecast
  • Operations management data interpretation

Precision Agriculture Applications

Precision agriculture (PA), or precision farming, is the management of fields at subfield level applying the right treatment, in the right amount, to the right place at the right time. In order to define all these parameters for the correct application, a series of sensors and other sources of information concerning the field(s) of interest are employed. iBO has the knowledge and expertise in PA applications using datasets acquired through the following sources:

  • Remote sensing. Satellite images are acquired and analysed deriving maps of various spectral indices related to plant and soil status.
  • Proximal sensing. The institute owns a range of proximal sensors for real time mapping of soil and crop attributes.
  • Wireless sensor systems. These are stationary sensors, positioned at selected locations, which measure in real-time weather and soil attributes that are useful for management decisions.

All the above mentioned layers of information are combined through Data Fusion procedures to support farmers in decision making. 


Agricultural environment awareness and perception

Agricultural operational environment structure demands from robotic systems to be configurable between different field layouts, soil types, and crop parameters (variety, size, maturity) and to be adaptable to different crops. This creates extensive intelligence requirements from agri-robotic systems.

iBO is specialized in research and development on agri-robotics awareness within agricultural environments and perception abilities for dedicated operational tasks including human-robot cooperative tasks.    

Indicative Projects


01/11/2017 - 31/10/2020


01/01/2020 - 31/12/2022


01/10/2019 - 30/09/2023


01/06/2019 - 31/05/2022