Synthesizing the Roughness of Textured Surfaces for an Encountered-Type Haptic Display Using Spatiotemporal Encoding
| Autor: | Siyeon Kim, Uran Oh, Yaesol Kim, Young J. Kim |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Surface finish Texture (music) Encoding (memory) 0202 electrical engineering electronic engineering information engineering Surface roughness Humans 0501 psychology and cognitive sciences Computer vision 050107 human factors ComputingMethodologies_COMPUTERGRAPHICS Haptic technology business.industry Orientation (computer vision) 05 social sciences 020207 software engineering Computer Science Applications Human-Computer Interaction Touch Perception Touch Robot Artificial intelligence business Texture synthesis |
| Zdroj: | IEEE Transactions on Haptics. 14:32-43 |
| ISSN: | 2334-0134 1939-1412 |
| DOI: | 10.1109/toh.2020.3004637 |
| Popis: | Encountered-type haptic rendering provides realistic, free-to-touch, and move-and-collide haptic sensation to a user. However, inducing haptic-texture sensation without complicated tactile actuators is challenging for encountered-type haptic rendering. In this article, we propose a novel texture synthesizing method for an encountered-type haptic display using spatial and temporal encoding of roughness, which provides both active and passive touch sensation requiring no complicated tactile actuation. Focused on macro-scale roughness perception, we geometrically model the textured surface with a grid of hemiellipsoidal bumps, which can provide a variety of perceived roughness as the user explores the surface with one's bare hand. Our texture synthesis method is based on two important hypotheses. First, we assume that perceptual roughness can be spatially encoded along the radial direction of a textured surface with hemiellipsoidal bumps. Second, perceptual roughness temporally varies with the relative velocity of a scanning human hand with respect to the surface. To validate these hypotheses on our spatiotemporal encoding method, we implemented an encountered-type haptic texture rendering system using an off-the-shelf collaborative robot that can also track the user's hand using IR sensors. We performed psychophysical user tests with 25 participants and verified the main effects of spatiotemporal encoding of a textured model on the user's roughness perception. Our empirical experiments imply that the users perceive a more rough texture as the surface orientation or the relative hand motion increases. Based on these findings, we show that our visuo-haptic system can synthesize an appropriate level of roughness corresponding to diverse visual textures by suitably choosing encoding values. |
| Databáze: | OpenAIRE |
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