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

A survey of real-time crowd rendering

In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft

Senescence: An Aging based Character Simulation Framework

The \u27Senescence\u27 framework is a character simulation plug-in for Maya that can be used for rigging and skinning muscle deformer based humanoid characters with support for aging. The framework was developed using Python, Maya Embedded Language and PyQt. The main targeted users for this framework are the Character Technical Directors, Technical Artists, Riggers and Animators from the production pipeline of Visual Effects Studios. The characters that were simulated using \u27Senescence\u27 were studied using a survey to understand how well the intended age was perceived by the audience. The results of the survey could not reject one of our null hypotheses which means that the difference in the simulated age groups of the character is not perceived well by the participants. But, there is a difference in the perception of simulated age in the character between an Animator and a Non-Animator. Therefore, the difference in the simulated character\u27s age was perceived by an untrained audience, but the audience was unable to relate it to a specific age group

Autonomous agents and avatars in REVERIE’s virtual environment

In this paper, we describe the enactment of autonomous agents and avatars in the web-based social collaborative virtual environment of REVERIE that supports natural, human-like behavior, physical interaction and engagement. Represented by avatars, users feel immersed in this virtual world in which they can meet and share experiences as in real life. Like the avatars, autonomous agents that may act in this world are capable of demonstrating human-like non-verbal behavior and facilitate social interaction. We describe how reasoning components of the REVERIE system connect and cooperatively control autonomous agents and avatars representing a user

Virtual humans: thirty years of research, what next?

In this paper, we present research results and future challenges in creating realistic and believable Virtual Humans. To realize these modeling goals, real-time realistic representation is essential, but we also need interactive and perceptive Virtual Humans to populate the Virtual Worlds. Three levels of modeling should be considered to create these believable Virtual Humans: 1) realistic appearance modeling, 2) realistic, smooth and flexible motion modeling, and 3) realistic high-level behaviors modeling. At first, the issues of creating virtual humans with better skeleton and realistic deformable bodies are illustrated. To give a level of believable behavior, challenges are laid on generating on the fly flexible motion and complex behaviours of Virtual Humans inside their environments using a realistic perception of the environment. Interactivity and group behaviours are also important parameters to create believable Virtual Humans which have challenges in creating believable relationship between real and virtual humans based on emotion and personality, and simulating realistic and believable behaviors of groups and crowds. Finally, issues in generating realistic virtual clothed and haired people are presente