Coordination of European Research on Industrial Safety towards Smart and Sustainable Growth
AIPER
AI-PowERed human-robot work environments for safe, healthy, and trustworthy collaboration
The increasing deployment of collaborative robots in industrial environments offers significant opportunities to improve productivity, flexibility and ergonomics, but also introduces new occupational safety challenges. Human–robot interaction can expose workers to physical, cognitive and psychosocial risks if not adequately designed and managed. Existing safety approaches often rely on static risk assessments and predefined safety zones, which are insufficient to address dynamic and complex work situations. There is a growing need for intelligent systems capable of supporting real-time risk assessment and adaptive safety management while maintaining operational efficiency. AIPER addresses this need by leveraging artificial intelligence to enhance safety, situational awareness and decision-making in human–robot work environments.
The project investigates how AI-based methods can be used to assess and manage safety risks in human–robot collaboration in real time. It explores how human behaviour, robot dynamics and environmental conditions can be monitored and integrated into adaptive safety systems. The project examines the role of AI in supporting operator awareness, decision-making and trust, as well as its impact on worker acceptance. Additional research questions address validation methodologies, system robustness, and alignment with existing safety standards and regulatory frameworks for collaborative robotics.
AIPER will deliver an AI-powered framework supporting safer human–robot collaboration in industrial environments. The project will develop methods for real-time risk monitoring, prediction and adaptive safety control. Demonstrators and validated industrial use cases will illustrate improvements in safety and operational performance. Outputs include technical guidelines, datasets and recommendations supporting the integration of AI-based safety solutions into industrial practice, standardisation activities and regulatory discussions.
The project is structured into five interlinked work packages. - WP1 – Project management and coordination: ensures overall project coordination, administrative management, quality control and dissemination activities. - WP2 – Analysis of human–robot interaction risks and requirements: identifies physical, cognitive and organisational risks associated with human–robot collaboration and defines operational safety requirements. - WP3 – Development of AI-based safety assessment methods: develops artificial intelligence methods for real-time monitoring, prediction and assessment of safety risks in human–robot work environments. - WP4 – System integration, validation and demonstration: integrates the developed AI-based safety methods into demonstrators and validates their performance in representative industrial scenarios. - WP5 – Dissemination, exploitation and standardisation: supports dissemination of results, industrial uptake and contribution to relevant standards and regulatory discussions.
INERIS
France
OSALAN
Spain
