SCA 15: Eurographics/SIGGRAPH Symposium on Computer Animation
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Browsing SCA 15: Eurographics/SIGGRAPH Symposium on Computer Animation by Subject "character animation"
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Item Hands On: Interactive Animation of Precision Manipulation and Contact(ACM Siggraph, 2015) Humberston, Ben; Pai, Dinesh K.; Florence Bertails-Descoubes and Stelian Coros and Shinjiro SuedaHumans show effortless dexterity while manipulating objects using their own hands. However, specifying the motion of a virtual character's hand or of a robotic manipulator remains a difficult task that requires animation expertise or extensive periods of offline motion capture. We present Hands On: a real-time, adaptive animation interface, driven by compliant contact and force information, for animating contact and precision manipulations of virtual objects. Using our interface, an animator controls an abstract grasper trajectory while the full hand pose is automatically shaped by proactive adaptation and compliant scene interactions. Haptic force feedback enables intuitive control by mapping interaction forces from the full animated hand back to the reduced animator feedback space, invoking the same human sensorimotor processes utilized in natural precision manipulations. We provide an approach for online, adaptive shaping of the animated manipulator based on prior interactions, resulting in more functional and appealing motions. The importance of haptic feedback for authoring virtual object manipulations is verified in a user study with nonexpert participants that examines contact force trajectories while using our interface. Comparing the quality of motions produced with and without force rendering, haptic feedback is shown to be critical for efficiently communicating contact forces and dynamic events to the user.Item Learning Reduced-Order Feedback Policies for Motion Skills(ACM Siggraph, 2015) Ding, Kai; Liu, Libin; Panne, Michiel van de; Yin, KangKang; Florence Bertails-Descoubes and Stelian Coros and Shinjiro SuedaWe introduce a method for learning low-dimensional linear feedback strategies for the control of physics-based animated characters around a given reference trajectory. This allows for learned low-dimensional state abstractions and action abstractions, thereby reducing the need to rely on manually designed abstractions such as the center-of-mass state or foot-placement actions. Once learned, the compact feedback structure allow simulated characters to respond to changes in the environment and changes in goals. The approach is based on policy search in the space of reduced-order linear output feedback matrices. We show that these can be used to replace or further reduce manually-designed state and action abstractions. The approach is sufficiently general to allow for the development of unconventional feedback loops, such as feedback based on ground reaction forces. Results are demonstrated for a mix of 2D and 3D systems, including tilting-platform balancing, walking, running, rolling, targeted kicks, and several types of ballhitting tasks.