Arash Mohtat

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Platforms capable of generating a rich haptic feedback are usually quite expensive and under strict proprietary protection. In addition, most of them are not portable and do not deliver a fully integrated force, tactile and visual user experience. In an attempt to break through these limitations, we have created the Haplet: an open-source, portable and(More)
In this paper, a nonlinear signal-processing scheme is developed for robotic systems that exploits a joint state-parameter formulation for simultaneous recursive estimation of the states (e.g. joint angles and rates) and uncertain parameters (e.g. inertial and friction parameters), out of noisy measurements (e.g. joint angles). Unscented Kalman filtering(More)
Enhancing the realism of the perceived contact force is a primary challenge in haptic rendering of virtual walls (VWs) and objects (VOs). For VOs, this goal directly translates into accurate rendering of not only stiffness, but also mass. The most challenging situation arises when the stiffness of the object is large, its mass is small, and sampling is(More)
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