Andrea Casalino
Politecnico di Milano, Consorzio di Bioingegneria e Informatica Medica
Papers
13
Total Citations
442
H-Index
9
About
Andrea Casalino is a robotics researcher whose work sits at the forefront of human–robot collaboration (HRC), with a particular focus on manufacturing and industrial assembly environments. His research addresses some of the most pressing challenges in modern automation: how robots and humans can share workspaces safely, efficiently, and intuitively in the era of Industry 4.0. Casalino's most influential contributions center on intelligent scheduling and activity prediction for collaborative tasks. His 2018 paper on predicting human activity patterns (134 citations) and his 2019 work on optimal scheduling using Time Petri Nets (113 citations) together establish a rigorous framework for managing the inherent variability of human behavior in joint assembly operations. These works have become foundational references in the HRC literature. Beyond planning and scheduling, Casalino has explored the human side of collaboration, notably through wearable vibrotactile feedback systems (82 citations) that keep operators situationally aware during robot co-working. His portfolio further spans proactive path planning, constraint-based liquid handling, fuzzy approaches to uncertain task durations, and occlusion-robust human pose estimation—reflecting a remarkably broad technical range. With over 430 cumulative citations, Casalino's body of work meaningfully advances both the theory and practice of safe, adaptive human–robot collaboration in real industrial settings.
Research Focus
Key Achievements
Top Papers
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- 4Human-robot collaborative assembly: a use-case application36 citations · 2018
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- 10Hybrid control of manipulators in human-robot coexistence scenarios3 citations · 2018