Real-Time Physics-Based 3D Biped Character Animation Using an Inverted Pendulum Model

We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

[1]  Jovan Popovic,et al.  Simulation of Human Motion Data using Short‐Horizon Model‐Predictive Control , 2008, Comput. Graph. Forum.

[2]  Jessica K. Hodgins,et al.  Interactive control of avatars animated with human motion data , 2002, SIGGRAPH.

[3]  Jessica K. Hodgins,et al.  Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces , 2004, ACM Trans. Graph..

[4]  Eugene Fiume,et al.  Physically Based Modeling and Control of Turning , 1993, CVGIP Graph. Model. Image Process..

[5]  Harry Shum,et al.  Motion texture: a two-level statistical model for character motion synthesis , 2002, ACM Trans. Graph..

[6]  Dinesh K. Pai,et al.  Post-stabilization for rigid body simulation with contact and constraints , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[7]  KangKang Yin,et al.  SIMBICON: simple biped locomotion control , 2007, ACM Trans. Graph..

[8]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  Taku Komura,et al.  Animating reactive motions for biped locomotion , 2004, VRST '04.

[10]  Marco da Silva,et al.  Interactive simulation of stylized human locomotion , 2008, ACM Trans. Graph..

[11]  F CohenMichael Interactive spacetime control for animation , 1992 .

[12]  Ambarish Goswami,et al.  A Biomechanically Motivated Two-Phase Strategy for Biped Upright Balance Control , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[13]  Kazuhito Yokoi,et al.  The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

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

[15]  Jessica K. Hodgins,et al.  Biped gait transitions , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[16]  Nancy S. Pollard,et al.  Efficient synthesis of physically valid human motion , 2003, ACM Trans. Graph..

[17]  Shinzo Kitamura,et al.  Motion generation of a biped locomotive robot using an inverted pendulum model and neural networks , 1990, 29th IEEE Conference on Decision and Control.

[18]  Jessica K. Hodgins,et al.  Motion capture-driven simulations that hit and react , 2002, SCA '02.

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

[20]  Jehee Lee,et al.  Precomputing avatar behavior from human motion data , 2004, SCA '04.

[21]  Jovan Popovic,et al.  Multiobjective control with frictional contacts , 2007, SCA '07.

[22]  David C. Brogan,et al.  Animating human athletics , 1995, SIGGRAPH.

[23]  C. Karen Liu,et al.  Learning physics-based motion style with nonlinear inverse optimization , 2005, ACM Trans. Graph..

[24]  Manoj Srinivasan,et al.  Computer optimization of a minimal biped model discovers walking and running , 2006, Nature.

[25]  Jessica K. Hodgins,et al.  Animation of dynamic legged locomotion , 1991, SIGGRAPH.

[26]  Philippe Beaudoin,et al.  Synthesis of constrained walking skills , 2008, SIGGRAPH Asia '08.

[27]  Marc Raibert Dynamic legged robots for rough terrain , 2010, 2010 10th IEEE-RAS International Conference on Humanoid Robots.

[28]  Philippe Beaudoin,et al.  Continuation methods for adapting simulated skills , 2008, ACM Trans. Graph..

[29]  C. Karen Liu,et al.  Animating responsive characters with dynamic constraints in near-unactuated coordinates , 2008, ACM Trans. Graph..

[30]  Arthur D. Kuo,et al.  Stabilization of Lateral Motion in Passive Dynamic Walking , 1999, Int. J. Robotics Res..

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

[32]  Jessica K. Hodgins,et al.  Adapting simulated behaviors for new characters , 1997, SIGGRAPH.

[33]  Jehee Lee,et al.  Simulating biped behaviors from human motion data , 2007, ACM Trans. Graph..

[34]  David Baraff,et al.  Fast contact force computation for nonpenetrating rigid bodies , 1994, SIGGRAPH.

[35]  Lucas Kovar,et al.  Motion graphs , 2002, SIGGRAPH '08.

[36]  I. Shimoyama,et al.  Dynamic Walk of a Biped , 1984 .

[37]  Bobby Bodenheimer,et al.  Synthesis and evaluation of linear motion transitions , 2008, TOGS.

[38]  Andy Ruina,et al.  Energetic Consequences of Walking Like an Inverted Pendulum: Step-to-Step Transitions , 2005, Exercise and sport sciences reviews.

[39]  Jerry Pratt,et al.  Velocity-Based Stability Margins for Fast Bipedal Walking , 2006 .

[40]  Marc H. Raibert,et al.  Legged Robots That Balance , 1986, IEEE Expert.

[41]  David J. Fleet,et al.  Physics-Based Person Tracking Using Simplified Lower-Body Dynamics , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[42]  Nancy S. Pollard,et al.  To appear in the ACM SIGGRAPH conference proceedings Responsive Characters from Motion Fragments , 2022 .

[43]  Jovan Popovic,et al.  Adaptation of performed ballistic motion , 2005, TOGS.

[44]  Petros Faloutsos,et al.  Composable controllers for physics-based character animation , 2001, SIGGRAPH.

[45]  Thomas W. Calvert,et al.  Goal-directed, dynamic animation of human walking , 1989, SIGGRAPH.

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