Principles of Humanoid Locomotion Control

July 12, 2011
Aaron Hertzmann | University of Toronto

Understanding the control forces that drive humans and animals is fundamental to describing their movement. Good models of control would be informative 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 and recognition in computer vision.

I will outline the main problems of human motion modeling, and describe some principles of humanoid motion 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 human movement.

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.

Speaker Details

Aaron Hertzmann recently completed his Ph.D at the Media Research Laboratory of the Courant Institute of Mathematical Sciences, New York University, working with Ken Perlin and Denis Zorin. Aaron received his BA in Computer Science and Art & Art History from Rice University in 1996, and his MS in Computer Science from NYU in 1998. He has worked at Microsoft Research, Mitsubishi Electric Research Lab, Interval Research Corporation and at NEC Research Institute. His thesis research concerns non-photorealistic rendering (synthesizing paintings, drawings, and animations); he is also interested in machine learning for computer graphics. Aaron’s homepage is at

http://www.mrl.nyu.edu/hertzmann/.