Luca Bascetta
Papers
50
Total Citations
1,245
H-Index
21
About
Luca Bascetta is a prominent robotics researcher whose work spans human-robot interaction, robot control, and surgical robotics. Based at the Politecnico di Milano, he has made significant contributions to making robots safer, more intuitive, and more capable of working alongside humans in shared environments. Bascetta's most influential work focuses on safety in industrial robotics, including a 2014 paper on distributed distance sensors for robot safety control (102 citations) and a 2011 study on visual tracking and intention estimation for human-robot collaboration (54 citations). He has also advanced the concept of human-like robot motion, developing redundancy resolution strategies that make industrial manipulators move more naturally and acceptably in shared workspaces, with related papers earning over 130 combined citations. His research extends into intuitive robot programming, particularly walk-through and lead-through programming techniques based on admittance control, enabling operators to guide robots without specialized expertise. More recently, Bascetta has contributed to surgical robotics, developing force control methods for minimally invasive surgery and manipulability optimization for robotic-assisted procedures. His exploration of aerial manipulation through nonlinear model predictive control further demonstrates the breadth of his impact. With over 600 cumulative citations, his work continues to shape the future of collaborative and medical robotics.
Research Focus
Key Achievements
Top Papers
- 1Safety Control of Industrial Robots Based on a Distributed Distance Sensor102 citations · 2014
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- 9Revising the Robust-Control Design for Rigid Robot Manipulators53 citations · 2009
- 10Nonlinear model predictive control for aerial manipulation52 citations · 2017