Yumi Kosemura

Characterization of surfaces virtually created using MEMS tactile display

In this paper, we report on the creation of a virtual surface using a MEMS tactile display and its quantitative analysis. The display consists of 3 ? 3 large-displacement MEMS actuators with hydraulic amplification mechanisms. The MEMS tactile display that we developed can create virtual surfaces that generate various tactile feelings at human fingertips by controlling the displacement, vibration frequency, and period of actuation of the actuators. To quantitatively characterize the virtually created surfaces, we newly proposed a sample comparison method. We compared the tactile feelings with those of 18 samples, such as wood, urethane foam, and sandpaper. These samples were characterized with respect to roughness and hardness using a laser microscope and a compression testing machine. The subjects were requested to select one of these samples that had a tactile texture most similar to the one created by the tactile display. From the experimental results, we could deduce a relationship between the driving conditions of the actuators and the roughness and hardness of the selected samples, and thus, the virtually created surfaces. We experimentally found that the displacement of actuators had a strong correlation with roughness whereas the display created hard surfaces under the tested driving conditions.

Quantitative analysis of surface textures created by MEMS tactile display using microfabricated tactile samples

This paper reports quantification of virtual surface textures produced by the MEMS_based tactile display. Tactile display consists of large displacement MEMS actuator array which is composed of piezoelectric actuators and hydraulic displacement amplification mechanism (HDAM) for large displacement to stimulate human tactile receptors. Tactile display can provide various surface textures such as “rough” “soft” “elastic” etc. to fingertip by controlling the voltages, the vibration frequencies and the time of actuators driving time. In previous work, we proved that tactile display could create smooth and rough textures by controlling the actuators parameters. In this study, to quantify tactile feelings virtually produced by the MEMS tactile display, we newly propose “Sample comparison method”. In this method, subjects require to compare between the virtual surface texture and tactile samples and select the sample most similar to displayed tactile feeling. In this paper, we firstly conducted comparing experiment using unprocessed samples to investigate what kind of surface characteristics can be controlled on the tactile display. Then, we experimented using microfabricated tactile samples to quantify the tactile feelings. At last, we successfully show the specific characteristics of surfaces virtually created by the MEMS tactile display.

Virtual Surface Textures Created by MEMS Tactile Display

This paper reports creation of virtual surface textures using a MEMS tactile display. The display consists of large-displacement MEMS actuators with hydraulic amplification mechanisms. By controlling the displacement, the vibration frequency, and actuator driving patterns, the display could generate tactile feeling of various surface textures to a fingertip. In order to investigate the produced virtual tactile sensation quantifically, we prepared 18 samples, such as wood, urethane foam, and sandpapers, to compare. The subjects were requested to select one of these samples that had a texture most similar to the one produced by the display. We categorized the samples with respect to roughness, softness, surface energy and warmness, and correlated the control parameters to the selected samples. We also used information amount to analyze the results with respect to shareness among the subjects. We experimentally found that displacement of actuators had strong correlation with the roughness and the display presented hard surfaces except when apparent motion was generated.

MEMS tactile display: from fabrication to characterization

We report fabrication and characterization of MEMS-based tactile display that can display users various tactile information, such as Braille codes and surface textures. The display consists of 9 micro-actuators that are equipped with hydraulic displacement amplification mechanism (HDAM) to achieve large enough displacement to stimulate the human tactile receptors. HDAM encapsulates incompressible liquids. We developed a liquid encapsulation process, which we termed as Bonding-in-Liquid Technique, where bonding with a UV-curable resin in glycerin is conducted in the liquid, which prevented interfusion of air bubbles and deformation of the membrane during the bonding. HDAM successfully amplified the displacement generated by piezoelectric actuators by a factor of 6. The display could virtually produce “rough” and “smooth” surfaces, by controlling the vibration frequency, displacement, and the actuation periods of an actuator until the adjacent actuator was driven. We introduced a sample comparison method to characterize the surfaces, which involves human tactile sensation. First, we prepared samples whose mechanical properties are known. We displayed a surface texture to the user by controlling the parameters and then, the user selects a sample that has the most similar surface texture. By doing so, we can correlate the parameters with the mechanical properties of the sample as well as find the sets of the parameters that can provide similar tactile information to many users. The preliminary results with respect to roughness and hardness is presented.

20pm3-PM013 Creation and evaluation of virtual surfaces by a tactile sensor coordination

In this paper, we demonstrate encoding of a surface texture and displaying it to a subject using a MEMS-based tactile display. The tactile display is composed of a piezoelectric actuator array and hydraulic displacement amplification mechanism. We now use the display to encode, or copy, the surface texture by sliding the surface on the display. The obtained waveforms from the piezoelectric actuator array, which worked as the sensor array, was, in turn, amplified to drive the actuator arrays to display the surface texture to the subject whose fingertip was placed onto the display. We successfully copied the surface textures of samples and could even blend the surfaces to create new surfaces with various hardness and roughness. The proposed system is readily applicable to advanced human-computer interactions.