Data-driven haptic modeling and rendering of deformable objects including sliding friction

This paper presents an extended data-driven haptic rendering method capable of reproducing force responses during sliding interaction on a large surface area. The core part of the approach is a novel input variable set for data interpolation model training, which includes the position of a proxy - the contact point on a surface when undeformed. This enables us to estimate friction in both sliding and sticking states. The behavior of the proxy is simulated in real-time based on a sliding yield surface - a cone-shaped surface separating the sliding and the sticking area in the external force space, identified through an automated palpation procedure. During modeling, input data and resultant force data are collected through manual palpation of a target object, which are used to build a radial-basis interpolation model. During rendering, this interpolation model with interaction inputs estimates force responses in real-time. Performance evaluation shows that our approach achieves reasonable estimation accuracy. This work is among the first attempts that fully support sliding exploration in the data-driven paradigm.