Efficient synthesis of physically valid human motion

Optimization is a promising way to generate new animations from a minimal amount of input data. Physically based optimization techniques, however, are difficult to scale to complex animated characters, in part because evaluating and differentiating physical quantities becomes prohibitively slow. Traditional approaches often require optimizing or constraining parameters involving joint torques; obtaining first derivatives for these parameters is generally an O(D2) process, where D is the number of degrees of freedom of the character. In this paper, we describe a set of objective functions and constraints that lead to linear time analytical first derivatives. The surprising finding is that this set includes constraints on physical validity, such as ground contact constraints. Considering only constraints and objective functions that lead to linear time first derivatives results in fast per-iteration computation times and an optimization problem that appears to scale well to more complex characters. We show that qualities such as squash-and-stretch that are expected from physically based optimization result from our approach. Our animation system is particularly useful for synthesizing highly dynamic motions, and we show examples of swinging and leaping motions for characters having from 7 to 22 degrees of freedom.

[1]  M Vukobratović,et al.  On the stability of biped locomotion. , 1970, IEEE transactions on bio-medical engineering.

[2]  Atsuo Takanishi,et al.  REALIZATION OF DYNAMIC WALKING BY THE BIPED WALKING ROBOT WL-10RD. , 1985 .

[3]  Roy Featherstone,et al.  Robot Dynamics Algorithms , 1987 .

[4]  Andrew P. Witkin,et al.  Spacetime constraints , 1988, SIGGRAPH.

[5]  Arun N. Netravali,et al.  Motion interpolation by optimal control , 1988, SIGGRAPH.

[6]  Eurographics Workshop on Animation and Simulation , 1990 .

[7]  Michael F. Cohen,et al.  Interactive spacetime control for animation , 1992, SIGGRAPH.

[8]  P. Toint,et al.  Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A) , 1992 .

[9]  Zicheng Liu,et al.  Hierarchical spacetime control , 1994, SIGGRAPH.

[10]  Michael F. Cohen,et al.  Decomposition of Linked Figure Motion: Diving , 1994 .

[11]  Michael Cohen,et al.  Keyframe Motion Optimization By Relaxing Speed and Timing , 1995 .

[12]  Norman I. Badler,et al.  Animating human locomotion with inverse dynamics , 1996, IEEE Computer Graphics and Applications.

[13]  Zicheng Liu,et al.  Efficient animation techniques balancing both user control and physical realism , 1996 .

[14]  Michael F. Cohen,et al.  Efficient generation of motion transitions using spacetime constraints , 1996, SIGGRAPH.

[15]  Michael Gleicher,et al.  Motion editing with spacetime constraints , 1997, SI3D.

[16]  Michiel van de Panne,et al.  From Footprints to Animation , 1997, Comput. Graph. Forum.

[17]  S. Shankar Sastry,et al.  Learning control of complex skills , 1998 .

[18]  Geoffrey E. Hinton,et al.  NeuroAnimator: fast neural network emulation and control of physics-based models , 1998, SIGGRAPH.

[19]  Zoran Popovic,et al.  Physically based motion transformation , 1999, SIGGRAPH.

[20]  H. Inoue,et al.  Dynamic walking pattern generation for a humanoid robot based on optimal gradient method , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[21]  Yoshihiko Nakamura,et al.  Making feasible walking motion of humanoid robots from human motion capture data , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[22]  Dimitris N. Metaxas,et al.  Recursive dynamics and optimal control techniques for human motion planning , 1999, Proceedings Computer Animation 1999.

[23]  Sung Yong Shin,et al.  A hierarchical approach to interactive motion editing for human-like figures , 1999, SIGGRAPH.

[24]  Steven M. Seitz,et al.  Interactive manipulation of rigid body simulations , 2000, SIGGRAPH.

[25]  Marcus G. Pandy,et al.  Dynamic Simulation of Human Movement Using Large-Scale Models of the Body , 2000, Phonetica.

[26]  G. Sohl,et al.  On the computation of optimal high-dives , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[27]  Nancy S. Pollard,et al.  Animation of Humanlike Characters: Dynamic Motion Filtering with a Physically Plausible Contact Model , 2001 .

[28]  Okan Arikan,et al.  Interactive motion generation from examples , 2002, ACM Trans. Graph..

[29]  C. Karen Liu,et al.  Synthesis of complex dynamic character motion from simple animations , 2002, ACM Trans. Graph..

[30]  Katsu Yamane,et al.  Dynamics Filter - concept and implementation of online motion Generator for human figures , 2000, IEEE Trans. Robotics Autom..