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About

Fabio Falezza is a leading researcher in surgical robotics, whose work bridges the critical gap between teleoperation and semi-autonomous systems. His primary research areas include multi-robot bilateral teleoperation, action segmentation for surgical assistance, and dynamic modeling of parallel robots. Falezza’s major contributions lie in developing architectures that enhance safety and autonomy in robotic-assisted minimally invasive surgery (R-MIS). His most cited work (29 citations) introduces a multi-modal learning system for controlling surgical assistant robots via action segmentation, paving the way for human-robot cooperation in high-precision tasks. He also proposed a novel two-layer bilateral teleoperation architecture for multi-arm systems, ensuring passivity and stability even with time delays. Falezza’s technical validation of a teleoperated multi-robot platform (19 citations) and his statechart-based modeling of surgical procedures (16 citations) are foundational for semi-autonomous robotic surgery. Additionally, his work on inverse dynamic models for delta robots and a time-of-flight stereoscopic endoscope for 3D anatomical reconstruction demonstrates his versatility in both hardware and software. With over 100 total citations, Falezza is shaping the future of safe, intelligent surgical robotics.