Rodolfo Zunino
Papers
8
Total Citations
229
H-Index
6
About
Rodolfo Zunino is a prominent researcher specializing in tactile sensing, computational intelligence, and embedded machine learning for robotics and human-robot interaction. His work sits at the intersection of artificial skin systems, robotic perception, and lightweight neural architectures, making significant contributions to how robots sense, interpret, and respond to physical contact with humans and objects. Zunino's most influential contribution, "Tactile-Data Classification of Contact Materials Using Computational Intelligence" (2011, 101 citations), established foundational methodologies for applying computational intelligence tools to robotic tactile sensing, demonstrating their suitability for processing complex sensor data. Building on this, he pioneered tensor-based pattern recognition frameworks for interpreting touch modalities in artificial skin systems, work that collectively garnered over 80 citations and advanced the field of electronic skin technology. More recently, Zunino has turned his attention to affordance segmentation and grasp classification for wearable and low-power robotic devices, addressing the critical challenge of deploying computationally demanding vision models on resource-constrained hardware. His ongoing exploration of lightweight neural networks and RGB-D camera integration reflects a commitment to making intelligent robotic perception practically deployable. With a career spanning hardware-software co-design challenges in robotics, Zunino's research continues shaping next-generation human-robot interaction systems.
Research Focus
Key Achievements
Top Papers
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- 4Computational Intelligence Techniques for Tactile Sensing Systems28 citations · 2014
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- 6Data-Driven Video Grasping Classification for Low-Power Embedded System6 citations · 2019
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