UROP Project
Building Neuromorphic Tactile Sensors for Robotics
Tactile Sensors, Robot, Human-Computer Interactions, Machine Learning, Fabrication
Research Mentor: Te-Yen Wu, Prof
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: tw23l@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: tw23l@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Computer Science, Electrical Engineering, Mechanical Engineering
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 10, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable
Number of Research Assistants: 2
Relevant Majors: Computer Science, Electrical Engineering, Mechanical Engineering
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 10, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable
Project Description
Traditional tactile sensing systems for robotics often rely on dense sensor arrays and complex wiring to retrieve high-resolution tactile information. As the sensing resolution increases, the number of electrical connections, data channels, and computational requirements can grow substantially, creating challenges in scalability, integration, and real-time processing, particularly for large-area or deformable robotic surfaces.This project explores approaches for integrating sensing and information-processing operations directly into the tactile sensor architecture. Inspired by how biological tactile receptors and peripheral neurons encode, transform, and transmit sensory information before it reaches the brain, we aim to develop tactile interfaces that perform part of the signal interpretation physically at the sensor level. Rather than transmitting every raw measurement independently, the proposed sensing architecture can encode salient tactile features into a reduced set of signals.
Research Tasks: literature review, prototype fabrication, data collection, data analysis
Skills that research assistant(s) may need: required: Arduino Programming, Electrical Knowledge
recommended: Machine Learning, 3D-printing Design