Near-optimal Character Animation with Continuous Control
We present a new model for real-time character animation with multidimensional, interactive control. The underlying motion engine is data-driven, enables rapid transitions, and automatically enforces foot-skate constraints without inverse kinematics. On top of this motion space, our algorithm learns approximately optimal controllers which use a compact basis representation to guide the system through multidimensional state-goal spaces. These controllers enable real-time character animation that fluidly responds to changing user directives and environmental constraints.
Project Members
Adrien Treuille
Yongjoon Lee
Zoran Popović
Near-optimal Character Animation with Continuous Control
Treuille, A. Lee, Y. Popović, Z.
ACM Transactions on Graphics 26(3) (SIGGRAPH 2007)
[Paper (0.8 Mb)]
SIGGRAPH video (5 mins) - (Requires Quicktime to view.)
[Movie (139.2 Mb)]
University of Washington Animation Research Labs
National Science Foundation
Alfred P. Sloan Fellowship
Intel Fellowship
Link Fellowship
Electronic Arts
Microsoft Research