Andrea Pupa
Papers
14
Total Citations
156
H-Index
7
About
Andrea Pupa is a robotics researcher specializing in human-robot collaboration (HRC), task scheduling, and safe motion planning for industrial environments. His work addresses one of modern robotics' most pressing challenges: enabling humans and robots to share workspaces efficiently, safely, and intelligently. Pupa's most significant contributions center on dynamic and resilient task scheduling architectures that adapt in real time to the uncertainties inherent in collaborative industrial settings. His 2021 paper on human-centered dynamic scheduling (43 citations) introduced a framework that optimally allocates tasks between human and robot partners across an entire work shift, while his 2022 follow-up (31 citations) extended this to handle unpredictable real-world disruptions. Complementing this scheduling research, he has developed sophisticated safety-aware motion planners that comply with ISO/TS 15066 regulations without sacrificing efficiency — a notoriously difficult balance. His work on energy tanks and closed-loop state sensitivity further demonstrates his depth in control theory and robust robot planning under model uncertainty. With over 140 cumulative citations across his published work and contributions spanning architecture design, trajectory optimization, and operator training, Pupa has established himself as an emerging authority bridging the gap between theoretical robotics and practical industrial deployment of collaborative systems.
Research Focus
Key Achievements
Top Papers
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- 4A Dynamic Planner for Safe and Predictable Human-Robot Collaboration14 citations · 2023
- 5A Time-Optimal Energy Planner for Safe Human-Robot Collaboration10 citations · 2024
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- 10Efficient ISO/TS 15066 Compliance through Model Predictive Control5 citations · 2024