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About

Giulio Di Gravio’s research lies at the critical intersection of human factors, systems engineering, and industrial robotics, with a particular focus on the safe integration of collaborative robots (cobots) into complex socio-technical work environments. His major contribution is the pioneering application of systems-theoretic safety analysis methods—specifically STPA (System-Theoretic Process Analysis) and interdependence analysis—to cobot applications. Rather than treating safety as a purely technical problem, Di Gravio frames human-robot collaboration as a joint cognitive system, where understanding interdependencies between human operators and machines is essential for both safety and efficiency. His most influential work, “Teaming with industrial cobots: A socio‐technical perspective on safety analysis” (70 citations), has become a foundational reference in the field, demonstrating how traditional safety approaches must be augmented with systems thinking to address emerging risks in human-robot teams. His subsequent studies on interdependence analysis in warehouse management and collaborative applications (cumulatively over 50 citations) have further advanced this framework, offering practical methodologies for designing safer, more effective human-robot work systems. Di Gravio’s work is essential reading for researchers and practitioners seeking to move beyond conventional safety standards toward a holistic understanding of cobot integration.