Learning to Navigate Cloth using Haptics

We present a controller that allows an arm-like manipulator to navigate deformable cloth garments in simulation through the use of haptic information. The main challenge of such a controller is to avoid getting tangled in, tearing or punching through the deforming cloth. Our controller aggregates force information from a number of haptic-sensing spheres all along the manipulator for guidance. Based on haptic forces, each individual sphere updates its target location, and the conflicts that arise between this set of desired positions is resolved by solving an inverse kinematic problem with constraints. Reinforcement learning is used to train the controller for a single haptic-sensing sphere, where a training run is terminated (and thus penalized) when large forces are detected due to contact between the sphere and a simplified model of the cloth. In simulation, we demonstrate successful navigation of a robotic arm through a variety of garments, including an isolated sleeve, a jacket, a shirt, and shorts. Our controller out-performs two baseline controllers: one without haptics and another that was trained based on large forces between the sphere and cloth, but without early termination.Comment: Supplementary video available at https://youtu.be/iHqwZPKVd4A. Related publications http://www.cc.gatech.edu/~karenliu/Robotic_dressing.htm

VISIO-HAPTIC DEFORMABLE MODEL FOR HAPTIC DOMINANT PALPATION SIMULATOR

Vision and haptic are two most important modalities in a medical simulation. While visual cues assist one to see his actions when performing a medical procedure, haptic cues enable feeling the object being manipulated during the interaction. Despite their importance in a computer simulation, the combination of both modalities has not been adequately assessed, especially that in a haptic dominant environment. Thus, resulting in poor emphasis in resource allocation management in terms of effort spent in rendering the two modalities for simulators with realistic real-time interactions. Addressing this problem requires an investigation on whether a single modality (haptic) or a combination of both visual and haptic could be better for learning skills in a haptic dominant environment such as in a palpation simulator. However, before such an investigation could take place one main technical implementation issue in visio-haptic rendering needs to be addresse

Research on real-time physics-based deformation for haptic-enabled medical simulation

This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

Soft volume simulation using a deformable surface model

The aim of the research is to contribute to the modelling of deformable objects, such as soft tissues in medical simulation. Interactive simulation for medical training is a concept undergoing rapid growth as the underlying technologies support the increasingly more realstic and functional training environments. The prominent issues in the deployment of such environments centre on a fine balance between the accuracy of the deformable model and real-time interactivity. Acknowledging the importance of interacting with non-rigid materials such as the palpation of a breast for breast assessment, this thesis has explored the physics-based modelling techniques for both volume and surface approach. This thesis identified that the surface approach based on the mass spring system (MSS) has the benefits of rapid prototyping, reduced mesh complexity, computational efficiency and the support for large material deformation compared to the continuum approach. However, accuracy relative to real material properties is often over looked in the configuration of the resulting model. This thesis has investigated the potential and the feasibility of surface modelling for simulating soft objects regardless of the design of the mesh topology and the non-existence of internal volume discretisation. The assumptions of the material parameters such as elasticity, homogeneity and incompressibility allow a reduced set of material values to be implemented in order to establish the association with the surface configuration. A framework for a deformable surface model was generated in accordance with the issues of the estimation of properties and volume behaviour corresponding to the material parameters. The novel extension to the surface MSS enables the tensile properties of the material to be integrated into an enhanced configuration despite its lack of volume information. The benefits of the reduced complexity of a surface model are now correlated with the improved accuracy in the estimation of properties and volume behaviour. Despite the irregularity of the underlying mesh topology and the absence of volume, the model reflected the original material values and preserved volume with minimal deviations. Global deformation effect which is essential to emulate the run time behaviour of a real soft material upon interaction, such as the palpation of a generic breast, was also demonstrated, thus indicating the potential of this novel technique in the application of soft tissue simulation

Design and development of a VR system for exploration of medical data using haptic rendering and high quality visualization

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Essential techniques for laparoscopic surgery simulation

Laparoscopic surgery is a complex minimum invasive operation that requires long learning curve for the new trainees to have adequate experience to become a qualified surgeon. With the development of virtual reality technology, virtual reality-based surgery simulation is playing an increasingly important role in the surgery training. The simulation of laparoscopic surgery is challenging because it involves large non-linear soft tissue deformation, frequent surgical tool interaction and complex anatomical environment. Current researches mostly focus on very specific topics (such as deformation and collision detection) rather than a consistent and efficient framework. The direct use of the existing methods cannot achieve high visual/haptic quality and a satisfactory refreshing rate at the same time, especially for complex surgery simulation. In this paper, we proposed a set of tailored key technologies for laparoscopic surgery simulation, ranging from the simulation of soft tissues with different properties, to the interactions between surgical tools and soft tissues to the rendering of complex anatomical environment. Compared with the current methods, our tailored algorithms aimed at improving the performance from accuracy, stability and efficiency perspectives. We also abstract and design a set of intuitive parameters that can provide developers with high flexibility to develop their own simulators