Upper Body Thermal Referral and Tactile Masking for Localized Feedback.

This paper investigates the effects of thermal referral and tactile masking illusions to achieve localized thermal feedback on the upper body. Two experiments are conducted. The first experiment uses a 2D array of sixteen vibrotactile actuators (4 × 4) with four thermal actuators to explore the thermal distribution on the user's back. A combination of thermal and tactile sensations is delivered to establish the distributions of thermal referral illusions with different numbers of vibrotactile cues. The result confirms that localized thermal feedback can be achieved through cross-modal thermo-tactile interaction on the user's back of the body. The second experiment is conducted to validate our approach by comparing it with thermal-only conditions with an equal and higher number of thermal actuators in VR. The results show that our thermal referral with a tactile masking approach with a lesser number of thermal actuators achieves higher response time and better location accuracy than thermal-only conditions. Our findings can contribute to thermal-based wearable design to achieve greater user performance and experiences.

Magnetorheological Fluid Haptic Shoes for Walking in VR.

In this article, present RealWalk, a pair of haptic shoes for HMD-based VR, designed to create realistic sensations of ground surface deformation, and texture using Magnetorheological fluid (MR fluid). RealWalk offers a novel interaction scheme through the physical interaction between the shoes, and the ground surfaces while walking in VR. Each shoe consists of two MR fluid actuators, an insole pressure sensor, and a foot position tracker. The MR fluid actuators are designed in the form of multi-stacked disc structure with a long flow path to maximize the flow resistance. With changing the magnetic field intensity in MR fluid actuators based on the ground material in the virtual scene, the viscosity of MR fluid is changed accordingly. When a user steps on the ground with the shoes, the two MR fluid actuators are pressed down, creating a variety of ground material deformation such as snow, mud, and dry sand. We built an interactive VR application, and compared RealWalk with vibrotactile-based haptic shoes in four different VR scenes: grass, sand, mud, and snow. We report that, compared to vibrotactile-haptic shoes, RealWalk provides higher ratings in all scenes for discrimination, realism, and satisfaction. We also report qualitative user feedback for their experiences.

Data-Driven Texture Modeling and Rendering on Electrovibration Display.

With the introduction of variable friction displays, either based on ultrasonic or electrovibration technology, new possibilities have emerged in haptic texture rendering on flat surfaces. In this work, we propose a data-driven method for realistic texture rendering on an electrovibration display. We first describe a motorized linear tribometer designed to collect lateral frictional forces from textured surfaces under various scanning velocities and normal forces. We then propose an inverse dynamics model of the display to describe its output-input relationship using nonlinear autoregressive neural networks with external input. Forces resulting from applying a pseudo-random binary signal to the display are used to train each network under the given experimental condition. In addition, we propose a two-step interpolation scheme to estimate actuation signals for arbitrary conditions under which no prior data have been collected. A comparison between real and virtual forces in the frequency domain shows promising results for recreating virtual textures similar to the real ones, also revealing the capabilities and limitations of the proposed method. We also conducted a human user study to compare the performance of our neural-network-based method with that of a record-and-playback method. The results showed that the similarity between the real and virtual textures generated by our approach was significantly higher.

Improving 3D Shape Recognition withElectrostatic Friction Display.

Electrovibration technology has the potential for seamless integration into ordinary smartphones and tablets to provide programmable haptic feedback. The aim of this work is to seek effective ways to improve 3D perception of visual objects rendered on an electrovibration display. Utilizing a gradient-based algorithm, we first investigated whether rendering only lateral frictional force on an electrovibration display improves 3D shape perception compared to doing the same using a force-feedback interface. We observed that although users do not naturally associate electrovibration patterns to geometrical shapes, they can map patterns to shapes with moderate accuracy if guidance or context is given. Motivated by this finding, we generalized the gradient-based rendering algorithm to estimate the surface gradient for any 3D mesh and added an edge detection algorithm to render sharp edges. Then, we evaluated the advantages of our algorithm in a user study and found that our algorithm can notably improve the performance of 3D shape recognition when visual information is limited.