Development of a physically behaved robot work cell in virtual reality for task teaching

Robot task teaching on a real work cell is expensive and sometimes risky. This cost and risk can be avoided by using virtual reality technology. Using the simulated environment in virtual reality (VR), the operator can practise, explore and preview the operations for possible problems that might occur during implementation. It is therefore of practical importance to build the virtual robot work cell in VR that can facilitate the study of the performance of robotic tasks such as robotic assembly. This paper describes our work in incorporating physical behaviours of virtual objects into VR for robot task teaching. To facilitate the task teaching, we developed visual and audio cues which help visualise the dynamic interactions between virtual objects. Dynamic sensing capability is incorporated in the simulated environment. A simplified force sensor is modelled and simulated. The physical behaviours of the virtual objects are simulated using physics-based approach. A virtual robot work cell is built incorporating the developed features and an example for the task teaching is given. The implementation includes view tracking using virtual camera, visual and audio rendering, and the user interface developed in the VR. The current implementation was carried out on a PC-based VR platform, with the programs developed using Watcom C++.     

基于深度图像序列的虚拟人蒙皮动画算法

虚拟人的蒙皮动画是虚拟人建模领域中的一个重要问题,在影视制作、动画设计、虚拟现实等应用中有着重大的价值。对于虚拟人蒙皮动画的研究,核心问题是蒙皮参数的计算,而蒙皮计算的准确与否决定了动画效果的逼真与否。常用的方法是根据骨骼与皮肤的距离进行直接计算,但是该方法对于姿态具有很大的依赖性,且没有定量的衡量标准,准确度难以保证。本文提出一种基于深度图像序列进行蒙皮参数优化计算的方法,该方法根据不同姿态下深度图像序列,设计关于蒙皮参数和姿态参数的优化函数,将不同姿态下的变形结果进行综合考虑,通过交替优化蒙皮参数和姿态参数,直到目标函数收敛,输出蒙皮参数。实验结果表明,与其他方法相比,本文方法在视觉上有更好的动画效果,在误差对比上,本文方法误差更小。     

基于DDA的碰撞检测及碰撞仿真

碰撞检测是基于物理的动画,计算机辅助没计,计算机辅助制造,计算几何,虚拟现实,机器人等领域必须解决的关键问题,目前仍是研究热点.非连续变形分析方法是一种较新的土木工程领域的数值模拟技术,可以分析不连续块体的运动.将非连续变形分析方法引入到基于物理动厕领域.在计算辅助设计软件设计的虚拟物理场景下,仿真了汽车撞墙和车辆相撞.仿真结果显示:应用非连续变形分析方法可以成功的实现精确的碰撞检测和模拟真实的碰撞响应,在不连续变形、多块体碰撞仿真方面有较大优势.     

Touch-enabled haptic modeling of deformable multi-resolution surfaces

Currently, interactive data exploration in virtual environments is mainly focused on vision-based and non-contact sensory channels such as visual/auditory displays. The lack of tactile sensation in virtual environments removes an important source of information to be delivered to the users. In this paper, we propose the touch-enabled haptic modeling of deformable multi-resolution surfaces in real time. The 6-DOF haptic manipulation is based on a dynamic model of Loop surfaces, where the dynamic parameters are computed easily without subdividing the control mesh recursively. A local deforming scheme is developed to approximate the solution of the dynamics equations, thus the order of the linear equations is reduced greatly. During each of the haptic interaction loop, the contact point is traced and reflected to the rendering of updated graphics and haptics. The sense of touch against the deforming surface is calculated according to the surface properties and the damping-spring force profile. Our haptic system supports the dynamic modeling of deformable Loop surfaces intuitively through the touch-enabled interactive manipulation.     

Functionality‐Driven Musculature Retargeting

We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and joint range of motion while preserving the functionality of the original musculature as closely as possible. The geometric configuration and physiological parameters of musculotendon units are estimated and optimized to adapt to new bodies. The range of motion around joints is estimated from a motion capture dataset and edited further for individual models. The retargeted model is simulation‐ready, so we can physically simulate muscle‐actuated motor skills with the model. Our system is capable of generating a wide variety of anatomical bodies that can be simulated to walk, run, jump and dance while maintaining balance under gravity. We will also demonstrate the construction of individualized musculoskeletal models from bi‐planar X‐ray images and medical examination.     

基于改进萤火虫算法的动态自动聚集路径规划方法*

针对群体动画中自动聚集场景的特点及现有方法中存在的计算代价高、行为单一、逼真程度不够、缺乏涌现特征的不足,提出了基于改进萤火虫算法的群体动态自动聚集路径规划方法。在群体自动聚集过程中,不但无须提前指定聚集目标点,而且根据外界环境的动态变化,自动寻找最优的聚集目标点。通过该方法可以为每个粒子生成运动路径,并能保证每次生成的聚集路径不完全一致,使制作的群体动画体现出群体运动的涌现特征,有效地提高群体动画的逼真效果。通过所开发的动态自动聚集路径规划系统有效地模拟群体聚集行为,验证了本方法的可行性和有效性。     

Accelerating Liquid Simulation With an Improved Data-Driven Method

In physics-based liquid simulation for graphics applications, pressure projection consumes a significant amount of computational time and is frequently the bottleneck of the computational efficiency. How to rapidly apply the pressure projection and at the same time how to accurately capture the liquid geometry are always among the most popular topics in the current research trend in liquid simulations. In this paper, we incorporate an artificial neural network into the simulation pipeline for handling the tricky projection step for liquid animation. Compared with the previous neural-network-based works for gas flows, this paper advocates new advances in the composition of representative features as well as the loss functions in order to facilitate fluid simulation with free-surface boundary. Specifically, we choose both the velocity and the level-set function as the additional representation of the fluid states, which allows not only the motion but also the boundary position to be considered in the neural network solver. Meanwhile, we use the divergence error in the loss function to further emulate the lifelike behaviours of liquid. With these arrangements, our method could greatly accelerate the pressure projection step in liquid simulation, while maintaining fairly convincing visual results. Additionally, our neutral network performs well when being applied to new scene synthesis even with varied boundaries or scales.     

Creation of a new set of dynamic virtual reality faces for the assessment and training of facial emotion recognition ability

The ability to recognize facial emotions is target behaviour when treating people with social impairment. When assessing this ability, the most widely used facial stimuli are photographs. Although their use has been shown to be valid, photographs are unable to capture the dynamic aspects of human expressions. This limitation can be overcome by creating virtual agents with feasible expressed emotions. The main objective of the present study was to create a new set of dynamic virtual faces with high realism that could be integrated into a virtual reality (VR) cyberintervention to train people with schizophrenia in the full repertoire of social skills. A set of highly realistic virtual faces was created based on the Facial Action Coding System. Facial movement animation was also included so as to mimic the dynamism of human facial expressions. Consecutive healthy participants (n = 98) completed a facial emotion recognition task using both natural faces (photographs) and virtual agents expressing five basic emotions plus a neutral one. Repeated-measures ANOVA revealed no significant difference in participants’ accuracy of recognition between the two presentation conditions. However, anger was better recognized in the VR images, and disgust was better recognized in photographs. Age, the participant’s gender and reaction times were also explored. Implications of the use of virtual agents with realistic human expressions in cyberinterventions are discussed.     

基于DI-Guy的人体视景仿真研究与应用

本文分析了目前几种典型的虚拟人系统,着重研究了基于DI-Guy的人体视景仿真技术,讨论了虚拟人的开发环境,分析了两种虚拟人生成方法（ACF配置实现及API编程实现）,论述了虚拟人实时运动中的若干问题;着重介绍了虚拟人自定义动作实时驱动方法,克服了用动作库中成型动作驱动的缺点,提高了人体视景仿真的真实性;给出了仓库调
调度仿真系统应用范例。结果表明,包含多个人体实体的虚拟场景在HP6200上的运行帧频大于28帧／秒,而且人体动静态效果逼真,满足一般工程应用需求。     

一种虚拟人运动生成和控制方法

利用运动捕获数据,通过学习获得虚拟人运动的统计模型,从而创建真实、可控的虚拟人运动.提出了一种方法:通过对原始运动数据聚类,提取出局部动态运动特征--动态纹理,并用线性动态系统描述,有选择地注释有明确含义的线性动态系统,构建注释动态纹理图.利用这一统计模型,可生成真实感强、可控的虚拟人运动.结果表明,这种方法在交互环境中能够生成流畅、自然的人体运动.