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Overview
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, as our testing report enhances credibility and opens doors to new market opportunities both locally and globally. Testing of devices with AI-integrated control systems by our LE.IA facility focuses on both performance and performance-related safety. Our tests, conducted under controlled laboratory conditions, ensure optimal reproducibility and repeatability, providing reliable insights into the system's efficiency and safety-critical functionalities.
More about the service
Discover more about our service, including how it can benefit you, the delivery process, and the options for customisation tailored to your specific needs!
This service can significantly benefit agricultural robotics and AI companies by ensuring their systems are reliable, efficient, and safe for real-world applications.
Performance Validation: The testing confirms that AI-driven agricultural robots perform optimally in various scenarios, such as autonomous navigation, picking tasks, and precise interventions. This boosts operational efficiency and productivity.
Safety Assurance: The focus on performance for safety ensures that robots meet the required safety standards, which is critical in environments where human workers, animals, or delicate crops are involved. This minimises risks and liability. Market Readiness: By obtaining LNE’s rigorous performance validation, agricultural robotics companies can demonstrate compliance with industry standards, gaining trust from clients and accelerating market adoption.
Reproducibility & Reliability: Testing in controlled conditions allows companies to fine-tune their AI models and robotic systems, ensuring consistent performance across different environments, which is essential for scaling operations in agriculture. This gives agricultural robotics firms a competitive edge, reinforcing the robustness and dependability of their products.
Performance Validation: The testing confirms that AI-driven agricultural robots perform optimally in various scenarios, such as autonomous navigation, picking tasks, and precise interventions. This boosts operational efficiency and productivity.
Safety Assurance: The focus on performance for safety ensures that robots meet the required safety standards, which is critical in environments where human workers, animals, or delicate crops are involved. This minimises risks and liability. Market Readiness: By obtaining LNE’s rigorous performance validation, agricultural robotics companies can demonstrate compliance with industry standards, gaining trust from clients and accelerating market adoption.
Reproducibility & Reliability: Testing in controlled conditions allows companies to fine-tune their AI models and robotic systems, ensuring consistent performance across different environments, which is essential for scaling operations in agriculture. This gives agricultural robotics firms a competitive edge, reinforcing the robustness and dependability of their products.
The service includes several technical meetings with AI and robotics evaluation experts to define the evaluation strategy and the procedure. Then, all the tests are realised at LNE, located in Trappes, France. Finally, a testing report is issued to the company. The overall process can take between 3 months and 12 months depending on the complexity of the system and the exhaustivity of the parameters to test.
The testing facility and the evaluation procedure and metrics are customised according to the customer needs of evaluation. Limitations lie in the dimensions of the physical device to host.
Location
France
Type of Sector
Arable farming
Food processing
Greenhouse
Horticulture
Livestock farming
Tree Crops
Viticulture
Type of service
Performance evaluation
Test design
Test execution
Test setup
Accepted type of products
Design / Documentation
Physical system
Software or AI model
