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About

Gerolamo Carboni is a robotics and human-robot interaction researcher whose work sits at the intersection of control theory, haptics, and motor learning. His research focuses on how humans and robots can physically collaborate more effectively, with particular emphasis on physical human-robot interaction, haptic communication, and motor assistance during rehabilitation and skill acquisition. Carboni's most influential contribution, "Differential game theory for versatile physical human-robot interaction" (2019, 131 citations), established a mathematically rigorous framework for modeling the cooperative dynamics between humans and robots as a game-theoretic problem — a significant conceptual advance in the field. Building on this foundation, his subsequent work has challenged conventional assumptions in robot-assisted training: he demonstrated that reactive robotic partners outperform passive guidance for motor learning (34 citations), and that humans actually prefer robotic assistance over assistance from unpredictable human partners (36 citations). His research has also shown that short time delays do not negate the benefits of haptic communication (26 citations), a practically important finding for teleoperation and remote collaboration. More recently, he has explored how humans modulate muscle impedance to optimize sensory perception. Collectively, his work has garnered over 250 citations, offering foundational insights that continue to shape the design of intelligent assistive and rehabilitative robotic systems.