Physically and perceptually based haptics

触觉技术旨在人工创造触摸物体的感觉。通过类比的方式，计算机图形学的目的是人为地创造看物体的感觉。例如，在医疗领域，触觉技术可以做出巨大贡献的例子比比皆是。它可以用于教学和培训，或远程执行医学，并应用于康复和治疗。在制造领域，触觉技术现在被应用于在制作物理模型之前对产品进行评估。我们将追求的一个应用是开发使盲人和视障人士能够获取图形信息的技术。将进行的研究旨在开发技术，使建立能够创建具有极大真实感的触觉模拟成为可能。我们将致力于扩展触觉合成技术，以创建由固体相互作用(粘性、可塑性、蠕变)的动力学产生的触觉信号，因为到目前为止，我们的技术仅适用于准静态情况。这项研究的另一个目标是开发能够提供类似于扫描表面时产生的皮肤感觉的技术，一个具体的例子是阅读盲文字符。同时，我们将寻求在触觉感知计算理论的发展方面取得进展。我们将考虑可用于恢复被触摸对象的属性的信息，并推导出大脑必须解决的问题才能恢复相关信息。然后就可以提出相应的计算问题了。由此，我们将做出更多的预测，并设计行为实验，通过系统地操纵参与解决原始问题的线索来测试这些预测。

Haptic technology aims at the artificial creation of the sensation of touching objects. By way of analogy, computer graphics aims at artificially creating the sensation of seeing objects. For example in the medical field, there are numerous instances where haptic technologies can contribute greatly. It can be used to teach and train, or to perform medicine remotely, and be applied to rehabilitation and therapy.  In manufacturing, haptic technologies are now applied to enable the assessment of products before physical mockups are made. One application which we will be pursuing is develop technology that will enable the blind and visually impaired access graphical information.The research to be carried out is aimed at the development of techniques that make it possible to build systems that can create haptic simulations having a great deal of realism. We will aim at expanding the techniques of haptic synthesis to create haptic signals that result from the dynamics of solid interaction (viscosity, plasticity, creep) since, to date, our techniques apply to quasi-static cases only. Another aim of the research will be the development of techniques that can provide cutaneous sensations which are similar to those arising when scanning surfaces, a specific example being reading Braille characters.In parallel, we will seek progress toward the development of a computational theory of haptic perception. We will consider the information that is available to recover the properties of the touched object and deduce the problems that must be solved by the brain to recover the relevant information. It will then be possible to pose the corresponding computational problems. From this,  predictions will be made and behavioral experiments will be designed to test them by systematic manipulation of the cues that participate in the solution of the original problem.