R. Petrigliano
Papers
1
Total Citations
75
H-Index
1
About
R. Petrigliano is a pioneering researcher in tactile sensing and robotic manipulation, with a primary focus on developing artificial systems that mimic human touch. His most influential work, "Detection of incipient object slippage by skin-like sensing and neural network processing" (1998), has garnered 75 citations and stands as a cornerstone in the field. Petrigliano’s major contribution lies in creating a neural network-based tactile system capable of detecting the earliest signs of object slippage—a critical capability for robots performing precise grasping and manipulation tasks. This innovation addresses a fundamental challenge in robotics: enabling machines to adaptively adjust grip before an object is dropped, much like human reflexes. Beyond slip detection, his research integrates fine-form reconstruction and primitive recognition, positioning his work as essential to the broader goal of artificial tactile intelligence. Petrigliano’s achievements have influenced subsequent developments in prosthetics, industrial automation, and human-robot interaction, making his contributions highly relevant for students and researchers exploring sensorimotor control and machine learning applications in robotics.
Research Focus
Key Achievements
Top Papers
- 1