To realize a telepresence system with tactile feedback and force feedback, real-time estimation of various tactile sensation must be conducted. Because several types of tactile sensation consist in touch and human tactile feeling has high time resolution. A man feels active touch extraordinary with time delayed transmission of tactile information. Our proposing human finger mimetic sensor covers three tactile factors, which are roughness, softness and friction of objects to touch. Current tactile telepresence systems represent just one tactile sensation in addition to kinesthetic information. For augmented reality, wider tactile factors must be sensed at a tactile sensor system and transferred to a tactile display system with small time delay. We realized quick estimation of vibrational frequencies of the sensor and softness of objects to regenerate touch feelings to human skin by tactile displays, which usually need time-consuming samples and make it hard to address tactile telepresence system. Quick estimation of vibrational frequency was conducted by emulating impulse emission of Meissner's corpuscles. Quick estimation of Young's modulus of objects was solved by computing strain distribution in a sensor

This paper discusses a novel approach in developing a texture sensor emulating the major features of a human finger. The aim of this study is to realize precise and quantitative texture sensing. Three physical properties, roughness, softness, and friction are known to constitute texture perception of humans. The sensor is designed to measure the three specific types of information by adopting the mechanism of human texture perception. First, four features of the human finger that were focused on in designing the novel sensor are introduced. Each feature is considered to play an important role in texture perception; the existence of nails and bone, the multiple layered structure of soft tissue, the distribution of mechanoreceptors, and the deployment of epidermal ridges. Next, detailed design of the texture sensor based on the design concept is explained, followed by evaluating experiments and analysis of the results. Finally, we conducted texture perceptive experiments of actual material using the developed sensor, thus achieving the information expected. Results show the potential of our approach.