Sophon Somlor
Papers
27
Total Citations
798
H-Index
13
About
Sophon Somlor is a robotics researcher whose work centers on tactile sensing, soft skin sensors, and intelligent robotic manipulation. He is best known for developing the **uSkin** sensor family — a series of compact, soft, distributed 3-axis force-sensitive electronic skins designed for integration on robot hands and humanoid platforms such as the iCub. His foundational papers on uSkin, published between 2016 and 2018, have collectively garnered over 400 citations, establishing him as a leading voice in robotic tactile hardware design. Somlor's early contributions explored Hall effect- and capacitive-based sensing principles, demonstrating practical pathways to affordable, digitally interfaced, multi-axis skin sensors. Beyond hardware, his research extends into the intelligent use of tactile data: he has investigated tactile object recognition, grasp stability prediction using spatio-channel-temporal attention networks, slip detection combining vision and touch, and ensemble learning frameworks for multi-phase grasping state perception. This progression from sensor design to data-driven manipulation reflects a cohesive research vision — equipping robots with human-like touch to enable safer, more dexterous interaction with unstructured environments. His work offers both foundational tools and applied algorithms that continue to influence the robotic sensing community.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Design and Characterization of a Three-Axis Hall Effect-Based Soft Skin Sensor106 citations · 2016
- 4A modular, distributed, soft, 3-axis sensor system for robot hands57 citations · 2016
- 5
- 6Detection of Slip from Vision and Touch34 citations · 2022
- 7A novel tri-axial capacitive-type skin sensor27 citations · 2015
- 8Development of a hall-effect based skin sensor26 citations · 2015
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