Claudio Coppola
Papers
13
Total Citations
144
H-Index
7
About
Claudio Coppola is a robotics and computer vision researcher whose work spans human activity recognition, robotic perception, and tactile sensing. He has made significant contributions to the field of social activity recognition, developing systems that leverage RGB-D data to identify human interactions and non-verbal communication patterns — research with direct implications for human-robot interaction. His foundational 2016 paper on probabilistic merging of skeleton features has garnered 33 citations, while subsequent work on continuous video-based social activity recognition demonstrates his commitment to translating laboratory methods into practical robotic applications. Beyond activity recognition, Coppola has expanded into robotic manipulation and sensory feedback, investigating grasp stability prediction through Bayesian exploration and depth vision, tactile slip detection in real-world settings, and soft electronic skin capable of multi-touch force estimation. His 2021 grasp stability work has attracted 16 citations, reflecting growing interest in dexterous autonomous manipulation. He has also contributed to human-to-robot handover challenges through the CORSMAL benchmark and explored accessible teleoperation systems incorporating haptic feedback. Collectively, his research addresses a broad but cohesive vision: equipping robots with the perceptual and tactile intelligence necessary to operate safely and effectively alongside humans in unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 3Social Activity Recognition on Continuous RGB-D Video Sequences19 citations · 2019
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- 5The CORSMAL Benchmark for the Prediction of the Properties of Containers9 citations · 2022
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- 9Volume-based Human Re-identification with RGB-D Cameras7 citations · 2017
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