About iRTA

iRTA aims to build a smart spraying apparatus tailored to the intricacies of treatment application in rough and steep slope terrains and on cultivations of high variability between plants, as is the grape. To achieve this, iRTA will combine state-of-the-art technologies with features that fully adhere to the requirements of the usage setting and integrate them into a flexible robotic platform. Namely, iRTA will augment the robotic platform with sophisticated software for autonomous localisation, navigation and obstacle avoidance, in order to enhance its traversability and ensure its safe operation in rough environments with the simultaneous presence of human workers.

The platform will be equipped with a high-precision, low-waste spraying component, further improved by the incorporation of advanced AI models for optimising treatment usage. The base platform itself will undergo improvements for increasing its efficiency and operational capacity.

The produced integrated platform will be thoroughly tested in both simulated and on-ground settings, in order to ensure that it meets the requirements posed by the tackled challenge. In parallel with technological advancements, the project will ensure that the iRTA solution has the appropriate visibility in relevant stakeholder communities and raise awareness for the product in carefully targeted markets. It will thus form the foundation for a successful commercialisation and lay out the plan for the sustainability of the platform after the end of the project.

iRTA Basics

Flexible and Modular Robotic Platform
able to move efficiently into the harsh agricultural environment
Autonomous Localization, Navigation and Obstacle Avoidance System

allowing the robot to plan and implement an optimal path and to safely operate in the presence of human workers

On-board Artificial Intelligence Component
analysing plant images in real-time as the robot traverses the field and decides on the application of treatment for individual plants and/or specific parts of them
high-end spraying system, able to apply pesticides in an accurate and efficient way


4 individual products will be developed

>30% of difference in labour costs and time needed compared with current labour costs

>4 ISO standards will be used

>50% of difference in money spent for buying spraying compounds, compared with conventional spraying


payload >100kg


>10% of difference in yield achieved compared with current agricultural practices


8 working hours without refueling


>60% reduction in fuel expenses, compared with conventional spraying


2 scientific papers will be published


complete solution final price <10.000€

Project Consortium

AGENSO is an innovative company and its team is composed of highly motivated and qualified people with extensive research experience in universities, companies and European projects. AGENSO having as main aim to exploit research ideas and products that were generated after many years of involvement in EU and National projects. Our team’s expertise spans in Precision Agriculture (PA) services and ICT solutions and specializes in the promotion of research and services in the areas of sustainable production and advanced technologies for agriculture. AGENSO is currently participating in eight (8) H2020 projects, 4 ICT-AGRI projects and 6 National projects for developing ICT solutions and software for agricultural and environmental domain. Moreover, AGENSO portfolio includes the development of an agricultural robot and various software applications. It also offers Precision Agriculture services to individual farmers and farmer’s cooperatives.

NCSR “Demokritos” is the largest self-governing research organization under the supervision of the General Secretariat for Research and Technology of the Greek Government. Demokritos conducts world-class basic and applied research for advancing scientific knowledge and for promoting technological development in selected areas of national socio-economic interest. Demokritos also plays a pivotal role in graduate education and professional training and its unique infrastructure is employed for high-technology services to industry and society. Demokritos participates to the project with the Software and Knowledge Engineering Lab (SKEL) of its Institute of Informatics and Telecommunications (II&T). SKEL has participated in and coordinated numerous national and European projects (Horizon 2020, FP7-ICT, FP6-IST, SIAP, DG-SANCO, bilateral) and has very substantial expertise in the areas of artificial intelligence and machine learning, data management and processing, machine perception, autonomous systems, language engineering, content analysis, and the Web.

Agricultural University of Athens (AUA) is the 3rd oldest University in Greece. Since 1920, contributes consistently and continuously to Greek and European primary sector development, by conducting basic and applied research in agricultural related sciences. AUA conducts the 1/3 of the agricultural research in Greece and counts 178 academic stuff, 300 supportive stuff, 5,000 students, 450 MSc students and 250 PhD students. The Precision Agriculture Lab, belonging to the department of Natural Resource Management and Agricultural Engineering, will represent AUA to the project. AUA’s Precision Agriculture team coordinates H2020 OPTIMA project developing a holistic solution on the disease elimination in vineyards, apples and carrots. It is a WP leader in the H2020 project BigDataGrapes (2018-2020) and participates as Regional Cluster Leader and Digital Innovation Hub in SmartAgriHubs and agROBOfood H2020 flagship projects. Members of the team have been participated in several National R&D programs on the application of novel / smart technologies in agriculture and in several European and bilateral programs.

SCiO is a deep-tech company, that provides innovative, world-leading, bespoke AI-enabled services for the disruption of the agri-food value chain. SCiO is based in Athens, Greece within the technology park of the National Centre for Scientific Research “Demokritos” (NCSR-D). SCiO specializes in different facets of data analysis from multi-parameter Descriptive Analytics to complex Predictive Analytics over large data volumes. Furthermore, it pushes the envelope on Prescriptive Analysis, building novel methodologies for determining, verifying and explaining analytical results. SCiO is thus able to provide innovative, world-leading, bespoke services that morph data into meaningful answers for practitioners and investors. SCiO was selected as finalist of the 2020 Syngenta Crop Challenge in Analytics, a competition that sought analytical approaches to improve complex crop breeding processes. Moreover, SCiO is one the recipients of the 2020 Elastic Search Awards under the cause category for developing GARDIAN, a data discovery framework built using Elasticsearch. The GARDIAN framework supports the CGIAR Platform for Big Data in Agriculture, a large-scale initiative to unlock important research publications and data sets about food security, nutrition, and natural resources.

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