Papers
7
Total Citations
72
H-Index
5
About
Elisa Beretta is a robotics researcher specializing in human-robot interaction, cooperative robotic surgery, and adaptive control systems. Her work focuses on developing intelligent robotic assistants that collaborate with surgeons during complex procedures, particularly in open-skull neurosurgery, where precision and safety are paramount. Beretta's most significant contributions center on advanced control architectures for surgical robotics. Her most-cited work (28 citations) introduced adaptive hands-on control using variable damping controllers that enable smooth, accurate tool placement during surgical targeting tasks. She further extended this research through enhanced torque-based impedance control approaches designed to improve positional accuracy during neurosurgical procedures, demonstrating their feasibility in clinically relevant scenarios. A recurring theme in her research is context-aware adaptability — enabling robots to seamlessly adjust their behavior in response to a surgeon's evolving needs without requiring explicit gestural commands. Her contributions to event-based behavior switching and gesteme-free adaptation represent meaningful steps toward more intuitive human-robot collaboration in the operating room. Beretta also advanced force feedback methodologies, including nonlinear schemes that enforce virtual boundaries on delicate brain tissue, helping protect patients during cortex stimulation procedures. With a publication record spanning 2014–2016 and growing citation impact, her work has meaningfully shaped the emerging field of cooperative surgical robotics.
Research Focus
Key Achievements
Top Papers
- 1Adaptive Hands-On Control for Reaching and Targeting Tasks in Surgery28 citations · 2015
- 2
- 3Event-based device-behavior switching in surgical human-robot interaction11 citations · 2014
- 4
- 5
- 6
- 7