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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 (Protoco 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.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

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

INRAE offers a comprehensive testing service to validate robot's safety functions in line with ISO 18497:2018.

Our tests assess robot's ability to detect and stop when encountering obstacles using a high-precision laser tracker for accuracy. These tests, conducted at our Montoldre site in France, will help ensure robot's compliance with industry safety standards.

A representative from the team must be present to assist in configuring and monitoring the system during testing.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test setup

Test execution

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.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

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.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

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.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

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

Laboratoire National de Métrologie 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.

Performance evaluation

Test design

Test execution

Test setup

Field Spectrometer Measurements

Instituut voor Landbouw-, Visserij- en Voedingsonderzoek

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.

Collection of test data

Conformity assessment

Desk assessment

Performance evaluation

Provision of datasets

Performance evaluation of AI and robotics based on physical testing environments

Laboratoire National de Métrologie et d’Essais - LNE

Performance evaluation

Test design

Test execution

Test setup

Provision of general-purpose datasets via a multisensory aerial robot.

National Institute for Research in Digital Science and Technology  - INRIA

We provide general-purpose datasets that can be used by customers to evaluate mobility algorithms and to develop and assess general-purpose AI applications. In the context of mobility algorithms, this pertains to classical robotics tasks such as mapping, localisation, and SLAM (Simultaneous Localisation and Mapping). Meanwhile, general-purpose AI applications focus on advancing algorithms and feeding decision support systems (DSS) for tasks including, but not limited to, weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas such as 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 robots, is crucial for developing efficient algorithms and AI solutions. Such datasets can support customers in 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

Provision of datasets

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

National Institute for Research in Digital Science and Technology  - INRIA

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

Provision of datasets

Provision of general-purpose datasets via multisensory ground robot

National Institute for Research in Digital Science and Technology  - INRIA

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 pertains to classical robotics tasks such as mapping, localisation, SLAM (Simultaneous Localisation and Mapping), and navigation. Meanwhile, general-purpose AI applications focus on advancing algorithms and feeding 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 monitoring these changes effectively. This real-time data collection, often facilitated by ground robots, 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

Provision of datasets

Testing and evaluating sensor devices

National Institute for Research in Digital Science and Technology  - INRIA

The SOPHIA infrastructure will offer the possibility to test and evaluate the performance of a sensor device in a locally controlled environment. While our indoor facility provides a fully controlled environment (light, volume), all facilities in SOPHIA can be customised to test and evaluate the sensor device. The service consists of three main steps. First, the sensor device will be integrated into the facility. After that, the facility will be customised according to the final application of the sensor device. Then, the performance of the sensor device will be evaluated using quantitative and qualitative metrics. Comparison could be proposed as a complementary option to position the performance of the sensor device in relation to the current state of the technology available in SOPHIA.

Collection of test data

Data analysis

Desk assessment

People training

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

Catalogue of Services

All agrifoodTEF services can be customised!

Which agrifood sector are you interested in?

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

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

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

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

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

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

Field Spectrometer Measurements

Performance evaluation of AI and robotics based on physical testing environments

Provision of general-purpose datasets via a multisensory aerial robot.

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

Provision of general-purpose datasets via multisensory ground robot

Testing and evaluating sensor devices

Interested in exploring the services from the agrifoodTEF Catalogue?

Catalogue of Services

All agrifoodTEF services can be customised!

Which agrifood sector are you interested in?

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

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

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

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

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

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

Field Spectrometer Measurements

Performance evaluation of AI and robotics based on physical testing environments

Provision of general-purpose datasets via a multisensory aerial robot.

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

Provision of general-purpose datasets via multisensory ground robot

Testing and evaluating sensor devices

Interested in exploring the services from the agrifoodTEF Catalogue?

Interested in exploring the services from the agrifoodTEF Catalogue?