Foldtac: Optical Tactile Sensing team will use computer vision techniques to build the next generation of tactile sensors

Faculty Mentors:


One major challenge in robotic sensing is building tactile sensors that is thin and have wide tactile sensing areas like human skins. A typical approach is to use deformable materials such as elastomers and use a camera to observe the deformation of the material via photometric stereo. However, as the camera has to be placed at a distance to the elastomer, it is difficult to make the sensor as flat as possible. The aim of this project is to develop a compact, vision-based tactile sensor for robots via folded optics. The research will involve two components as follows:

  • Design and build a tactile sensor prototype with appropriate light sources and flat elastomers.
  • Make an experimental platform that can properly calibrate the sensor using computer vision techniques.


Relevant Technologies:

  • Computer vision
  • Machine learning
  • Computational sensing

Pre-requisite knowledge/skills:

Signal processing, machine learning, computer vision.