Feature-Based Locomotion Controllers for Physically-Simulated Characters Aaron Hertzmann, Adobe Understanding the control forces that drive humans and animals is fundamental to describing their movement. Although physics-based methods hold promise for creating animation, they have long been considered too difficult to design and control. Likewise, recent results in computer vision suggest how physical models, if developed, could be important to human pose tracking. I will describe the main problems of human motion modeling. I will then present a new approach to control of physics-based characters based on high-level features of human movement. These controllers provide unprecedented flexibility and generality in real-time character control: they are capture many natural properties of human movement; they can be easily modified and applied to new characters; and they can handle a variety of different terrains and tasks, all within a single control strategy. Until very recently, even making a controller walk without falling down was extraordinarily difficult. This is no longer the case. Our work, together with other recent results in this area, suggests that we are now ready to make great strides in locomotion.