Catalogue of Services

National Institute for Research in Digital Science and Technology  (INRIA)

Provision of general-purpose datasets with user-specified sensor(s)

General-purpose datasets serve two primary objectives: (i) evaluating mobility algorithms and (ii) developing and assessing general-purpose AI applications. In the context of mobility algorithms, this includes classical robotics tasks such as mapping, localisation, SLAM (Simultaneous Localisation and Mapping), and navigation. Meanwhile, general-purpose AI applications focus on advancing algorithms and supporting decision support systems (DSS) for tasks such as, but not limited to, weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas like arable farming, horticulture, food processing, forestry, and tree management. A significant challenge in developing AI solutions for agricultural robotics lies in the dynamic nature of agricultural environments, which fluctuate with different seasons and weather conditions. To address this, acquiring consistent and periodic data is essential for effectively monitoring these changes. This real-time data collection, often facilitated by aerial and/or ground robots equipped with user-specified sensors, is crucial for developing efficient algorithms and AI solutions. Such datasets can support the development of sensor-specific techniques or be leveraged to create multisensory algorithms, enabling more accurate and adaptable systems for agricultural applications.

Data analysis

Data augmentation

Desk assessment

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Provision of real-time data streams

The service provides access to data streams collected from equipment tested by other services or using specially installed sensor or camera arrays in specific test environments. It includes the provision of data streams from sensors and cameras installed to meet specific customer needs in agreed areas and tailored to work in these specific locations. Such areas are, for example, fields, orchards, vineyards, forests, or specific locations such as farms, barns, or warehouses. Furthermore, the service includes access to corrections from local RTK stations and meteorological station data. In this way, it provides comprehensive and reliable data access support for a variety of customer requirements.

Qualification of trajectory execution accuracy of livestock robots

ARPA PC2 thoroughly evaluates how well agricultural robots can follow established paths in indoor and outdoor environments. This service helps ensure that robots can successfully navigate various settings typical of a farm, including any obstacles and transitions between spaces they might face. ARPA PC2 provides essential information about the robot's accuracy and behaviour while moving by testing in real-life conditions. This assessment enhances operational reliability and safety and supports manufacturers in optimising their robots for improved performance in diverse agricultural scenarios.

Test design

Danish Technological Institute (DTI)

Safety and Regulatory Testing for Agricultural Robotics

This service offers a thorough examination of agricultural robots, focusing on safety validation under diverse operational conditions. It tests stopping distances and response times for mobile robots across various speeds and payloads. Regulatory compliance is assessed to ensure adherence to industry standards. The service utilizes a controlled testing environment that simulates agricultural field conditions, equipped with measurement tools to analyze stopping distances and robot dynamics. Parameters can be adjusted to test different speeds, payloads, and environmental factors, minimizing risks and enhancing reliability in dynamic farm environments.

University of Cordoba (UCO)

Conformity assessment

Satellite: Evaluation of results of physical testing

This service offers an evaluation of satellite-derived data quality by applying performance metrics that assess model reliability and effectiveness. The service includes a comprehensive analysis of test data and previously collected ground truth data to validate the performance of models used in precision agriculture. With a detailed performance report, clients receive valuable insights that support model improvement and informed decision-making in agricultural management.

Fondazione Bruno Kessler (FBK)

Test design

Setup for AI solution testing

Digital testing of an AI solution often requires action to obtain the proper configuration. This service contains all the required actions necessary to configure, integrate and execute the client AI solution with FBK test environment. Carrying out these preliminary activities, FBK will be able to have a working setup that will be the entry point for subsequent testing and validation services.

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Support for testing safety devices for safe obstacle avoidance by autonomous vehicles

Our service offers to provide specialised support for evaluating the behaviour of a self-moving robot or autonomous vehicle. As part of the service, the equipment and control systems will be verified for the maintenance of operational safety rules by analysing the correctness of stopping in front of obstacles. For this purpose, an advanced testing methodology based on the provisions of ISO 18497 will be used. During the tests, specialised equipment will be used to control the maintenance of the linearity of vehicle travel. Support will be tailored to the customer's needs in terms of providing the required control equipment and elements necessary for proper testing, such as model obstacles. These activities lead to increased automation efficiency and precision of controlled objects in agricultural applications.

Conformity assessment

Test design

Politecnico di Milano (POLIMI)

Support in interconnecting systems to AgrifoodTEF’s computational test infrastructure

Università degli Studi di Milano (UMIL)

Digital testing requires interaction among several different components which have to reliably cooperate to enable the testing activities and to ensure that their outcomes reliably reflect the system’s capabilities. When digital testing of customer systems leverages agrifoodTEF’s computational infrastructure, integration between the infrastructure and the systems to be tested is needed before the tests/experiments can be executed. If the customer does not possess the technical expertise – or does not want to devote resources – to perform the integration, this service can support them in the process. Help is provided by a team of expert engineers.

This service concerns the integration of the customers’ system and/or data used for testing with the agrifoodTEF digital testing infrastructure. In particular, integration is crucial to ensure smooth and uninterrupted communication between the system and the infrastructure that produces, collects and/or processes test data.

This service also includes the development of any custom components needed to ensure a two-way integration between the system and the reference infrastructure (e.g., software components to format data or to perform transcoding).

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Technology advancement and readiness assessment

Poznan Supercomputing and Networking Center (PSNC)

Wielkopolska Agricultural Advisory Center in Poznań (WODR)

This service helps you understand where your AI-powered product, system, or software stands in terms of technological maturity. We conduct a basic, yet structured evaluation of your solution—including physical testing of selected components and general system behaviour—to identify its current development stage and key areas that need improvement. We also assess the quality of documentation, system architecture, and software implementation. For example, when evaluating an apple-picking robot, we assess the readiness and integration of its core subsystems: the gripper mechanism, robotic arm kinematics and control, and the vision system responsible for detecting ripe fruit. We analyse areas where current solutions can be improved or require some redesign and whether the robot as a whole can effectively perform “scene ”cleaning”—removing ripe apples while preserving unripe ones and the plant structure. Based on our findings, we prepare a clear roadmap and a development plan with recommendations for the next steps, which may include further testing or refinement through other agrifoodTEF services. As part of the process, we also confirm the current Technology Readiness Level (TRL) of each major component. The outcome helps you focus your R&D work and understand what is still required to move your solution closer to full deployment and commercial readiness.

Conformity assessment

Test and development of innovative and practical agri-food applications of the metaverse

Università degli Studi di Napoli (UNINA)

The service enables agri-food industry stakeholders to harness the power of the metaverse to innovate, collaborate, and solve challenges in new and exciting ways. It creates immersive virtual environments within the metaverse that replicate real-world agri-food settings, such as farms, processing facilities, and marketplaces. These environments serve as digital replicas where stakeholders can interact, collaborate, and experiment. By leveraging immersive virtual environments and cutting-edge technology, it empowers farmers and operators to stay at the forefront of agri-food innovation in the digital age.

Interested in this service? Contact us at angrisan@unina.it

AI model training

Data analysis

Data augmentation

Centre d'Estudis Porcins (CEP)

Test and validate intelligent solutions based on sensors to optimise livestock farming

Universitat de Lleida (UdL)

The service validates that the tested solution performs as expected by the vendor or manufacturer. The objective is to detect potential mistakes in the sensor readings, the processing of the signal gathered by the sensor or in the intelligent component deriving the final information to be provided to the user to optimise livestock farming . The test can be performed at sensor or application level. The tests and validation can be performed in a laboratory or in an experimental pig farm equipped with automatic and manual measures of different variables (feed, water, CO2, NH3, temperature, ventilation, liveweight, etc.)