Papers

16

Total Citations

377

H-Index

9

About

Matteo Parigi Polverini’s research lies at the critical intersection of human-robot collaboration, safety, and dexterous manipulation. His work is defined by a rigorous, model-driven approach to ensuring that robots can work safely alongside humans and perform complex assembly tasks without expensive external sensors. He introduced the concept of a “kinetostatic safety field” for real-time collision avoidance, a foundational contribution that has garnered 49 citations, and developed computationally efficient safety assessments for collaborative robotics (67 citations). Polverini also pioneered sensorless force control strategies for precision tasks like peg-in-hole insertion (48 citations), and his hierarchical, data-driven control architectures (39 citations) have advanced implicit force control. His research extends to whole-body loco-manipulation, demonstrated in the multi-contact pushing of heavy objects with a centaur-type humanoid robot (44 citations). By developing pre-collision control strategies based on dissipated energy in potential impacts (37 citations) and constraint-based programming for assembly skills (28 citations), Polverini has systematically addressed the core challenges of safe, autonomous, and sensor-efficient robotic interaction, establishing himself as a key contributor to the practical realization of collaborative and humanoid robotics.

Research Focus

Key Achievements

9
H-Index
16
Papers
377
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
A computationally efficient safety assessment for collaborative robotics applications
67 citations · 2016
📈 Most Prolific Year: 2019 (5 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Politecnico di Milano, Consorzio di Bioingegneria e Informatica Medica, Italian Institute of Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago