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Wolfram Summer School

June 24–July 14, 2018
Bentley University, Waltham, MA

Alumni

Teja Vodlak

Wolfram Science

Class of 2015

Bio

Teja Vodlak is a PhD student at Swansea University, United Kingdom, a Marie Curie fellow on the Prototouch ITN project. After she finished her BCs in applied mathematics at the University of Ljubljana, Slovenia, in 2011, she gained a position as a research assistant on the FP7 NanoBioTouch project at the same university. She stayed there for two years, and in January 2014, Teja moved to Swansea, where she enrolled in the PhD program in civil engineering. Currently, her research interest focuses mostly on computer modeling of human touch, namely, modeling of tactile contact, by employing multi-scale multi-physics simulations in order to bridge the gap between mechanical stimulation and spike generation for the virtual prototyping and optimization of tactile displays.

Project: Tactile Information Encoding

The aim of the project is to develop an approach for encoding physical texture for virtual representation. Taking inspiration from the RGB additive color model, the idea is to find an analogous model for encoding physical texture and quantify it with a set of parameters.

Virtual Representation of the Texture - FPA encoding

Since it has been shown that a texture can be encoded by spatial spectrum in terms of lateral force, the approach applied here proposes representation of the texture as a triplet of the following parameters:

  • Frequency: function of relative position—spatial dependency
  • Amplitude: function of frequency and relative position
  • Phase: function of frequency and relative position

Analogously to display devices, the virtual surface (e.g. a tactile display) needs first to be discretized into taxels (tactile pixels), and each taxel is assigned a different 3-tuple of parameters—frequency, amplitude, and phase.

Output of the model: texture in terms of {frequency, amplitude, phase, time, relative position} = {𝜈, a, 𝜑, t, r(x,y)} for each taxel.

Protocol for texture encoding

Images

Input data: physical texture (left) and recording of lateral force versus distance