A haptic content resource built from one hundred everyday textures and data-driven models of their stiffness, friction, and surface texture.
As the lack of haptic contents is one of the limitations of current haptics technology, this research aims at developing a hardware and software framework for efficient haptic model building based on actual measurement data. In this work, we develop and integrate data-driven haptic contents modeling methods for stiffness, friction, and surface texture, and construct The Haptic Library. Then, we seek new perception- and image-based techniques to automatically assign the acquired models to 3D mesh models.
Researchers: Waseem Hassan, Arsen Abdulali, and Seokhee Jeon
Funding: part of 촉감표준융합연구단 (Meta-Touch Research Group), funded by NST Korea.
The Haptic Library consists of one hundred textures from everyday life, commonly encountered during daily interactions. Each texture comes with data-driven models of its haptic properties, organised in three sub-libraries: