Catalogue of Services

Data augmentation

ARPA 1 - Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497:2024 reference obstacle)

We offer a comprehensive testing service to validate the safety functions of autonomous mobile robots and robotic systems. Our tests use a high-precision laser tracker for accuracy to assess your robot's ability to detect and stop when encountering an obstacle, as defined in ISO 18497:2024 (Protocol included in part IV Annex D.2).

These tests, conducted at our Montoldre site in France, will help ensure your robot's compliance with industry safety standards. A representative from your team must be present to assist in configuring and monitoring the system during testing.

ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)

This service tests the performance of on-board detection systems in agricultural robots, focusing on their safety functions under challenging environmental conditions like fog and rain. Conducted at the PAVIN platform in Clermont-Ferrand, France, the tests evaluate sensor accuracy and response, identifying any false negatives or positives. A manufacturer's representative must be present to configure the system and ensure proper operation during testing.

ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)

This service evaluates the effectiveness of onboard geofencing safety systems in agricultural robots, ensuring they stay within designated work areas as required by ISO 18497:2024. The test involves the robot following various trajectories that challenge boundary limits. High-precision monitoring ensures compliance, with the robot required to enter a safe state if it breaches the boundary. A manufacturer's representative must be present to oversee the process.

ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)

The ARPA 4 test thoroughly evaluates the safety systems of agricultural robots, focusing on their ability to detect human-like obstacles and automatically stop to prevent accidents. It simulates real-world scenarios by positioning mannequins in front of the robot as it moves through artificial crop rows. Using a high-precision laser tracking system, the test measures the robot’s trajectory and speed at our Montoldre site in France. This ensures the robot can safely operate in environments like vineyards or orchards, providing valuable insights into its emergency stop functions and compliance with safety standards. A manufacturer’s representative must oversee the process.

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

Assessment of AI and robotic solutions for testing

Josephinum Research (JR)

RISE - Research Institutes of Sweden

This service includes all essential actions to gather knowledge, design, and document the client’s needs regarding Testing and Experimentation Facility (TEF) services. Through close collaboration with the client, we ensure that all technical, operational, and methodological aspects are clearly outlined, forming a solid foundation for future testing phases. By conducting these preparatory activities, we deliver a comprehensive setup analysis that serves as the entry point for subsequent testing and validation services and provision of datasets. This ensures that testing can be carried out efficiently, aligning with the client’s specific requirements while leveraging TEF’s expertise and infrastructure. Ultimately, this service streamlines the testing process, reduces uncertainties, and enhances the overall efficiency of AI and robotic solution validation.

Wageningen University WUR

Assessment of interoperability for AI-driven solutions

Data interoperability in the agrifood sector hinders innovation and development due to the need for many custom solutions to share data. This service helps agricultural organisations improve how they handle and share data across the entire food value chain. By implementing standardised reference data models like rmAgro (https://rmagro.org), we help to optimise your data flows and make your information systems work better together. Our team at Wageningen Research provides expert guidance in data modelling and implements reference models that align with industry standards and tests the reference models against various use cases. This promotes more efficient data sharing between different systems and organisations, reducing data integration challenges and improving operational efficiency. The service is particularly valuable for organisations looking to modernise their data infrastructure or needing to share data more effectively with partners in the agri-food sector. This service provides an assessment of interoperability for AI-driven solutions within the agri-food sector. The service facilitates conformance testing and verification of whether the related IT systems comply with relevant standards, guidelines, data space regulations, and other interoperability requirements. By evaluating the IT systems against established reference data models and frameworks like rmAgro (https://rmagro.org), the service ensures that it meets the necessary criteria for effective data sharing and integration. Wageningen Research leverages its expertise to evaluate the overall AI solution on its quality, performance, and how well it aligns with industry standards, offering insights and recommendations for improvement. This service supports organisations in ensuring their solutions are interoperable, compliant, and ready for seamless integration within the agri-food value chain.

Conformity assessment

Evaluation for Ethical, Legal, and Social Aspects (ELSA Scan) for responsible AI development

Wageningen University WUR

What are the ethical, legal, and social aspects (ELSA) of AI-driven technology in agri-food? Mitigation of potential risks and finding opportunities are easier by identifying ELSA aspects in early development stages, when the technology is still in the making. Examples of ELSA aspects are autonomy, transparency, and bias, but also data privacy and other legal aspects. How does your AI technology deal with ELSA aspects? A combined survey and interview help AI developers to identify opportunities and issues with ELSA in the agri-food context from the perspective of end users and more broadly, for society. For example, to better align with the sustainability objectives of the AI-driven technology. The outcomes of the ELSA scan are a list of identified key ELSA aspects and high-level recommendations to further improve the AI technology.

ELSA assessment

Evaluation of AI performance based on mixed testing environments

Laboratoire National de Meterologie et d'Essais (LNE)

By having your AI system tested by the LNE, you ensure it meets the highest standards of safety and performance, boosting your product’s reliability and trustworthiness in the market. Partnering with the LNE for rigorous testing of your AI technologies and a detailed evaluation report used for demonstrating performance enhances credibility and opens doors to new market opportunities both locally and globally. This service proposes to assess a range of agricultural devices (with respect to the physical constraints of the testing bench) integrating AI, particularly those utilising vision processing, within our advanced hybrid testing environment. Our novel hybrid testing facility consists of placing devices in the heart of a simulation projected onto a 300° screen while a motion capture system and instrumented conveyor belt measure its movements, if any. These data are continuously sent to the simulator in real time so that the device's digital twin follows the same movements and the projected environment is updated accordingly. The simulator also incorporates a physics engine and advanced sensor models, enabling a virtual sensor output to be substituted for the sensors in real time in the cases where devices require specific data and/or if the assessment is orientated toward a special kind of sensor degradation. Typical agricultural products evaluated include mobile robots for autonomous weeding or harvesting that use visual navigation (based on 2D cameras) and intelligent cameras (with AI functionalities) for crop health monitoring or livestock tracking. Other sensors commonly used in agriculture, such as 3D cameras for yield estimation, GPS for autonomous vehicle control, Lidar for terrain mapping, and sonar for obstacle detection, are also supported through data injection from the simulator.

Laboratoire National de Meterologie et d'Essais (LNE)

Evaluation of technical and regulatory aspects for robotic devices or AI systems

No matter the stage in your product's life cycle, LNE supports your project with any required study or regulatory assistance. This service provides you with the know-how of its AI evaluation teams through a range of expertise to answer your needs of understanding the normative landscape and related testing possibilities. Our specialised technical and regulatory service delivers a meticulous evaluation of your robotic device or AI-based software, highlighting critical areas of concern and optimising compliance with European regulation (e.g., AI Act, Machine Regulation, Cyber Resilience Act, ...) and industry standards (ISO 18497, IEC 61508, ...). LNE offers tailored support throughout your product’s life cycle, utilising our expertise to address industrial challenges. Related to your AI or robotic solution, we will investigate and report the standards identified and their requirements to help you better understand and implement them. This service can optionally propose a blank audit to assess any discrepancies and implement corrective actions before certification. Visit the Website for more information.

Desk assessment

ELSA assessment

LCA assessment

Evaluation of the energy efficiency of the embedded hardware associated with the AI functionality

Laboratoire National de Meterologie et d'Essais (LNE)

By having your AI or robotic system tested by LNE, you ensure it meets the highest standards of safety and performance, boosting your product’s reliability and trustworthiness in the market. Partnering with LNE for rigorous testing of your robotic and AI technologies gives you a competitive edge and trusted third-party assessment that enhances your product credibility and opens doors to new market opportunities both locally and globally. This service provides testing of devices with AI-integrated control systems, focusing on energy efficiency and consumption during the product life cycle. By simulating a wide range of scenarios, we provide detailed insights into the energy performance of these AI systems with regard to their expected operational environment. These tests can be conducted under different conditions, either in a completely simulated way, through a hybrid test bench where the actual physical device is assessed within a simulated environment, or using physical infrastructures based on the device's operational environment to test it in a 'real' setting. Tests are conducted under controlled laboratory conditions, ensuring optimal reproducibility and repeatability, providing reliable insights into the system's efficiency and safety-critical functionalities. Typical assessments may cover the energy efficiency of SLAM, various types of end effectors, and other relevant components such as sensors, motors or AI software. This rigorous testing process helps identify potential areas for improvement, enabling companies to enhance the efficiency and sustainability of their products, ultimately leading to cost savings and reduced environmental impact.

Instituut voor Landbouw-, Visserij- en Voedingsonderzoek (ILVO)

Field Spectrometer Measurements

This service utilises field spectrometers to measure the spectral properties of physical environments, such as barns, greenhouses, or outdoor fields. By capturing detailed spectral data, we help you develop, improve, or validate your agri-food solutions, whether for monitoring plant health, optimising lighting conditions, or enhancing environmental control systems. The measurements provide insights into how different wavelengths of light interact with the environment, enabling fine-tuned adjustments for better crop growth, energy efficiency, or precision farming applications. Additionally, this service can serve as a follow-up to lab-scale measurements where hyperspectral technology is used to conduct pilot tests to determine which wavelengths provide valuable information. In this service, we then perform field tests on these specific wavelengths.

Conformity assessment

Desk assessment