Matteo Pecorella
Papers
2
Total Citations
29
H-Index
2
About
Matteo Pecorella is a leading researcher at the intersection of surgical robotics, augmented reality (AR), and human-robot collaboration. His work focuses on enhancing precision and safety in minimally invasive procedures, particularly in urology. Pecorella’s major contributions include the development of an AR and human-robot collaboration framework for percutaneous nephrolithotomy (PCNL), a complex kidney stone removal surgery. This system, detailed in his 2024 paper (16 citations), assists surgeons in defining incision points and aligning needles to preplanned paths, reducing reliance on manual ultrasound or fluoroscopy. He also created a Unity-based da Vinci robot simulator for surgical training (2022, 13 citations), addressing the growing demand for low-cost, open-source simulation platforms in Robot-Assisted Minimally Invasive Surgery (RAMIS). With over 29 citations across his top works, Pecorella’s innovations are shaping the future of surgical training and intraoperative guidance, offering practical solutions that improve both surgeon skill development and patient outcomes. His work exemplifies how AR and robotics can transform traditional surgical workflows into safer, more efficient procedures.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Unity-based Da Vinci Robot Simulator for Surgical Training13 citations · 2022