Understanding the control forces that drive humans and
animals is fundamental to describing their movement. Good models of control
would be useful for many fields. Although physics-based methods hold promise
for creating animation, they have long been considered too difficult to design
and control. Likewise, physical motion models, if developed, could be very
valuable to human pose tracking in computer vision.
I will outline the main problems of human motion
modeling, and describe some principles of humanoid control from the
biomechanics literature. Based on these principles, I will then present a new
approach to control of physics-based characters based on high-level features of
These controllers provide unprecedented flexibility and
generality in real-time character control: they 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.