ARTWORK — The Smart and Connected Worker
ArtWork develops a real-time, context-aware assistance system for industrial workers. The project combines digital twins, smart instruction generation, and worker feedback systems to connect workers to the production line and enable automatic derivation of process instructions based on context.
The solution targets four industrial use cases across truck assembly, textile manufacturing, ship engine manufacturing, and bus assembly — demonstrating the system in real production environments across Europe.
Infotiv’s contribution: Human-robot collaboration simulation (RITA-SIM), worker pose capture and replay, and integration of the SIMLAN multi-camera framework.
🔗 artworkproject.org · 🔗 Vinnova
SMILE III & IV — Safety Analysis of ML-Based Systems
Future autonomous vehicles rely on Deep Machine Learning (DML) algorithms whose correct behaviour cannot be guaranteed by traditional software engineering approaches. The SMILE projects develop methods that allow DML-based functions to be included in safety-critical vehicular applications while meeting quality control requirements from industrial standards such as ISO 21448 (SOTIF) and ISO 26262.
SMILE III focused on establishing safety analysis methods for ML components. SMILE IV extends this work toward formal safety cases and tool-supported assurance workflows.
Infotiv’s contribution: Application of the AMLAS framework to the SMIRK pedestrian emergency braking demonstrator; development of safety cases for ML components.
VALU3S — Verification and Validation of Automated Systems
VALU3S is a large-scale European research project that designs, implements, and evaluates state-of-the-art V&V methods and tools for automated systems across multiple safety-critical domains.
The consortium spans 40 partners from 10 countries, including 24 industrial partners from automotive, agriculture, railway, healthcare, aerospace, and industrial automation, alongside 6 leading research institutes and 10 universities.
Infotiv’s contribution: Search-based software testing of the Baidu Apollo autonomous driving platform in the SVL simulator; evolutionary test case generation for pedestrian detection.