Enrico Di Lello
Papers
5
Total Citations
157
H-Index
5
About
Enrico Di Lello is a robotics researcher whose work sits at the critical intersection of industrial automation, human safety, and intelligent perception. His primary research areas include human-robot interaction (HRI), Bayesian nonparametric modeling, and fault detection in robotic systems. Di Lello’s most influential contribution, "Towards safe human-robot interaction in robotic cells," proposes a vision-based safety controller that tracks human presence and estimates intention—a foundational step toward removing physical safety fences and enabling true collaboration between humans and industrial robots. This work has garnered over 87 combined citations, reflecting its importance in the field of safe robotics. Complementing this, his 2013 paper on Bayesian time-series models for continuous fault detection (48 citations) demonstrates how Hierarchical Dirichlet Process Hidden Markov Models can learn sensor signatures and classify anomalies in real robotic assembly tasks, eliminating the need for cross-validation. Di Lello also contributed to domestic robotics with the PEIS Table, an autonomous robotic table for home environments. Through his research, Di Lello has advanced both the safety and intelligence of robotic systems, bridging the gap between industrial rigor and adaptive, human-aware automation.
Research Focus
Key Achievements
Top Papers
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- 5The PEIS Table: An Autonomous Robotic Table for Domestic Environments10 citations · 2011