Evaluation and Optimization of a Multi-Point Tactile Renderer for Virtual Textures
Date: 22 October 2013
Thesis or dissertation
University of Exeter
PhD in Physics
The EU funded HAPTEX project aimed to create a virtual reality system that allowed a user to explore and manipulate a suspended virtual textile with the thumb and index finger. This was achieved through a combination of a tactile renderer on the fingertips for surface textures and a force feedback system for deformation of the virtual ...
The EU funded HAPTEX project aimed to create a virtual reality system that allowed a user to explore and manipulate a suspended virtual textile with the thumb and index finger. This was achieved through a combination of a tactile renderer on the fingertips for surface textures and a force feedback system for deformation of the virtual material. This project focuses on the tactile rendering component of this system, which uses a tactile display developed at the University of Exeter. The 24 pin display is driven by piezoelectric bimorphs. Each of the pins can be driven independently, allowing for a variety of different sensations to be transmitted to the fingertip. The display is driven by rendering software that uses a spatial spectrum of the intended surface, in combination with the frequency response of touch receptors in the skin, position on the surface, and exploration velocity to produce a signal that is intended to recreate the sensation of exploring the surface texture. The output signal on each of the 24 contactors is a combination of high (320 Hz) and low (40 Hz) frequency sine waves. In this project, the tactile renderer is initially evaluated based on its ability to recreate the sensations of exploring particular textured surfaces. The users were asked to rank virtual textures in order of similarity to a real target texture. The results of the initial test were disappointingly low, with a 38.1±3.1% correct identification rate. However, feedback from this initial test was used to make improvements to the rendering strategy. These improvements did not give a significant improvement in identification (41.3±1.6%). Finally, the tests were repeated with a target virtual texture instead of the real one used in previous tests. This test yielded a higher identification rate (64.1±5.5%). This increase in identification suggests that the virtual textures are distinguishable but that they not always accurate recreations of the real textures they are mimicking.
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