Data-based dynamic haptic interaction model with deformable 3D objects

The data-based modeling of the haptic interaction simulation is a growing trend in research. These techniques offer a quick alternative to parametric modeling of the simulation. So far, most of the use of the data-based techniques was applied to static simulations. This paper introduces how to use data-based model in dynamic simulations. This ensures realistic behavior and produce results that are very close to parametric modeling. The results show that a quick and accurate response can be achieved using the proposed methods.

Data-driven computation of contact dynamics during two-point manipulation of deformable objects

This study represents a preliminary step towards data-driven computation of contact dynamics during manipulation of deformable objects at two points of contact. A modeling approach is proposed that characterizes the individual interaction at both points and the mutual effects of the two interactions on each other via a set of parameters. Both global as well as local coordinate systems are tested for encoding the contact mechanics. Artificial neural networks are trained on simulated data to capture the object behavior. A comparison of test data with the output of the trained system reveals a mean squared error percentage between 1% and 3% for simple interactions.

Physically based simulation of heterogeneous deformable models using XFEM

This paper addresses the problem of heterogeneous deformable model accuracy using the finite element methods (FEM). Classic FEM uses predefined shape functions for interpolation and does not account easily for regions of discontinuities. Extended finite element methods (XFEM) use enrichment functions to compensate for the change in an element degrees of freedom (DoFs) in deformable objects. The XFEM is an accurate and fast method as no remeshing is required. In this study we investigate the performance of XFEM and demonstrate how it may be applied to discontinuities of materials that exist in heterogeneous (piece-wise homogeneous) models. The results show realistic stress prediction compared to modeling the same objects with classic FEM.

Towards an efficient haptic rendering using data-driven modeling

This thesis focuses on the optimisation of haptic rendering of interactions with deformable models. The research demonstrated that data-driven techniques can produce a real-time, accurate and complex simulation experience. Applications include, but not limited to, virtual training, rapid prototyping, virtual presence, and entertainment.