A novel approach to modelling and simulating the contact behaviour between a human hand model and a deformable object

A deeper understanding of biomechanical behaviour of human hands becomes fundamental for any human hand-operated Q2 activities. The integration of biomechanical knowledge of human hands into product design process starts to play an increasingly important role in developing an ergonomic product-to-user interface for products and systems requiring high level of comfortable and responsive interactions. Generation of such precise and dynamic models can provide scientific evaluation tools to support product and system development through simulation. This type of support is urgently required in many applications such as hand skill training for surgical operations, ergonomic study of a product or system developed and so forth. The aim of this work is to study the contact behaviour between the operators’ hand and a hand-held tool or other similar contacts, by developing a novel and precise nonlinear 3D finite element model of the hand and by investigating the contact behaviour through simulation. The contact behaviour is externalised by solving the problem using the bi-potential method. The human body’s biomechanical characteristics, such as hand deformity and structural behaviour, have been fully modelled by implementing anisotropic hyperelastic laws. A case study is given to illustrate the effectiveness of the approac

SmartSIM - a virtual reality simulator for laparoscopy training using a generic physics engine

International audienceVirtual reality (VR) training simulators have started playing a vital role in enhancing surgical skills, such as hand–eye coordination in laparoscopy, and practicing surgical scenarios that cannot be easily created using physical models. We describe a new VR simulator for basic training in lapa-roscopy, i.e. SmartSIM, which has been developed using a generic open‐source physics engine called the simulation open framework architecture (SOFA). This paper describes the systems perspective of SmartSIM including design details of both hardware and software components, while highlighting the critical design decisions. Some of the distinguishing features of SmartSIM include: (i) an easy‐to‐fabricate custom‐built hardware interface; (ii) use of a generic physics engine to facilitate wider accessibility of our work and flexibility in terms of using various graph-ical modelling algorithms and their implementations; and (iii) an intelligent and smart evaluation mechanism that facilitates unsupervised and independent learning

Development of a learning from demonstration environment using ZED 2i and HTC Vive Pro

Being able to teach complex capabilities, such as folding garments, to a bi-manual robot is a very challenging task, which is often tackled using learning from demonstration datasets. The few garment folding datasets available nowadays to the robotics research community are either gathered from human demonstrations or generated through simulation. The former have the huge problem of perceiving human action and transferring it to the dynamic control of the robot, while the latter requires coding human motion into the simulator in open loop, resulting in far-from-realistic movements. In this thesis, a novel virtual reality (VR) framework is proposed, based on Unity’s 3D platform and the use of HTC Vive Pro system, ZED mini, and ZED 2i cameras, and Leap motion’s hand-tracking module. The framework is capable of detecting and tracking objects, animals, and human bodies in a 3D environment. Moreover, the framework is also capable of simulating very realistic garments while allowing users to interact with them, in real-time, either through handheld controllers or the user’s real hands. By doing so, and thanks to the immersive experience, the framework gets rid of the gap between the human and robot perception-action loop, while simplifying data capture and resulting in more realistic samples. Finally, using the developed framework, a novel garment manipulation dataset will be recorded, containing samples with data and videos of nineteen different types of manipulation which aim to help tasks related to robot learning by demonstrationObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur