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Physical Testing of Endurance & Reliability

Lukasiewicz Poznanski Instytut Technologiczny

We provide physical testing services, both in laboratory and field environments, to evaluate the endurance and reliability of devices and their components. These tests focus on the ability of components to withstand external conditions while maintaining proper functionality. Our testing process helps identify potential weaknesses in device design, offering insights that can inform adjustments to algorithms or hardware. The service is designed to ensure your systems can perform reliably under a variety of conditions, helping to prevent failures and maintain optimal performance in real-world applications.

Collection of test data

People training

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

Preparation of computational test environment

Politecnico di Milano (POLIMI)

To successfully conduct a digital testing campaign, preparatory activities are usually required to set up the computational environment used for testing. This service performs activities such as: - setting up the hardware resources needed to run the tests - configuring and initialising the virtual environments used for testing (e.g., Docker images, private “data rooms” for safe data sharing) - installation and configuration of required software packages and dependencies - Setting up authentication layers, user roles and credentials as needed- Migration and/or exchange of required data and ground truth annotations - installation and configuration of a simulator - importing and configuring a previously defined simulated environment - executing dry runs to check that all elements of the test environment operate as required Environment preparation is done according to an environment design provided by the customer. If needed, such design can be done by AgrifoodTEF for the customer via Service S00176. Interested customers can get support from AgrifoodTEF for the entire pipeline involved in digital testing, from the design of its other elements beside the environment (namely, the testing protocol via service S00177 and the evaluation metrics via service S00178) to test execution (service S00182) and data collection (service S00183) and evaluation (S00184). Support in interconnecting the systems under test to the digital testing environment, if needed, is available via service S00181.

Test setup

Preparation of physical test environment

Politecnico di Milano (POLIMI)

Testing a system in a physical environment requires an environment that has been prepared and set up to support the specific testing activities to be executed. This service supports the customer in the execution of the tests by taking care of such preparation and setup. The service involves: - agronomic preparation: e.g., providing the required soil conditions, making sure that a given in-field configuration of specific plants at a given growth stage is available at the time of testing, and so on; - Technical preparation: e.g., setting up infrastructure elements such as RTK GPS base stations, environmental sensors, power and networking, as well as the computational environment required to interface with the system under test to acquire and possibly pre-process experimental data. If AgrifoodTEF facilities are involved in the experimental activities, the service also includes configuring the testing facility accordingly. Environment preparation is done according to an environment design provided by the customer. If needed, such a design can be done by AgrifoodTEF for the customer via Service S00106. Interested customers can get support from AgrifoodTEF for the entire pipeline involved in experimental testing, from the design of its other elements beside the environment (namely, the testing protocol via service S00107 and the evaluation metrics via service S00108) to test execution (service S00113), data collection (service S00113), and evaluation (S00114). The output of Service S00110 is the environment ready for the execution of the testing campaign at the time requested by the customer.

Test setup

Provision of datasets

Politecnico di Milano (POLIMI)

During the development of systems based on AI and/or robotics, tailored data are needed to support the realisation, validation and optimisation of systems and subsystems. This service aims at providing such data. AI models are a noteworthy example of systems that require data to be trained; more generally, any system which processes data produced via artificial perception (such as images, videos, LiDAR, ultrasound, radar...) requires suitable data to be built, tested and fine-tuned. This service allows a customer to define together with AgrifoodTEF the specific features of the data that the customer’s activities require and to receive datasets precisely matching such features. Among the features to be defined are the type, number and specifications of the data streams comprised in the datasets (e.g., when multi-sensor data are required) and the range of variations encompassed by the data (e.g., variety of environmental conditions represented in a sensor stream); lower-level features to be defined concern formatting and packaging of the data.

Provision of datasets

Provision of general-purpose datasets via multisensory ground robot

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

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

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)

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 real-time data streams

Lukasiewicz Poznanski Instytut Technologiczny

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.

Collection of test data

Provision of datasets

Safety and Regulatory Testing for Agricultural Robotics

Danish Technological Institute (DTI)

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.

Collection of test data

Conformity assessment

Support in interconnecting systems to AgrifoodTEF’s computational test infrastructure

Politecnico di Milano (POLIMI)

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).

Test execution

Test setup

Support in interconnecting systems to physical infrastructure

Politecnico di Milano (POLIMI)

Testing a system in a physical environment requires an environment that has been prepared and set up to support the specific testing activities to be executed. Such an environment usually involves both agronomy-related elements (machines, fields, greenhouses, cultivations...) and technical infrastructure (sensors, networks, software, logging systems...). In order to execute the testing, the physical system under test (e.g., an agricultural robot) must correctly interface with all these elements; this service takes care of ensuring this. For instance, it is crucial to ensure that the communication between the system under test and the technical infrastructure supporting the testing activities is correct, smooth and uninterrupted. Wherever needed, the service also includes the development of custom components needed to ensure a successful two-way integration between the system and the testing infrastructure (e.g., a software component to format data or perform transcoding). While available separately, this service is often used in association with service S00110 (Preparation of physical test environment).

Test setup

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

Università degli Studi di Napoli Federico II

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

Collection of test data

Data analysis

Data augmentation

Performance evaluation

Test execution

Catalogue of Services

All agrifoodTEF services can be customised!

Which agrifood sector are you interested in?

Physical Testing of Endurance & Reliability

Preparation of computational test environment

Preparation of physical test environment

Provision of datasets

Provision of general-purpose datasets via multisensory ground robot

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

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

Provision of real-time data streams

Safety and Regulatory Testing for Agricultural Robotics

Support in interconnecting systems to AgrifoodTEF’s computational test infrastructure

Support in interconnecting systems to physical infrastructure

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

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?

Physical Testing of Endurance & Reliability

Preparation of computational test environment

Preparation of physical test environment

Provision of datasets

Provision of general-purpose datasets via multisensory ground robot

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

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

Provision of real-time data streams

Safety and Regulatory Testing for Agricultural Robotics

Support in interconnecting systems to AgrifoodTEF’s computational test infrastructure

Support in interconnecting systems to physical infrastructure

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

Interested in exploring the services from the agrifoodTEF Catalogue?

Interested in exploring the services from the agrifoodTEF Catalogue?