Control policies trained using deep reinforcement learning often generate stiff, high-
frequency motions in response to unexpected disturbances. To promote more natural and …

Synthesizing realistic human movements, dynamically responsive to the environment, is a
long-standing objective in character animation, with applications in computer vision, sports …

We present an approach for training" agile" character control policies, able to produce a
wide variety of motor skills from a single reference motion cycle. Our technique builds off of …

The movement process of organisms contains a large amount of information, which leads to
different structure of motion data in different applications. How to construct a data structure to …

Creating digital twins of humans and robots in physics simulations has widespread
applications in both digital and real-world domains, including gaming, 3D content …