SIMBICON: simple biped locomotion control

ABSTRACT

Physics-based simulation and control of biped locomotion is difficult because bipeds are unstable, underactuated, high-dimensional dynamical systems. We develop a simple control strategy that can be used to generate a large variety of gaits and styles in real-time, including walking in all directions (forwards, backwards, sideways, turning), running, skipping, and hopping. Controllers can be authored using a small number of parameters, or their construction can be informed by motion capture data. The controllers are applied to 2D and 3D physically-simulated character models. Their robustness is demonstrated with respect to pushes in all directions, unexpected steps and slopes, and unexpected variations in kinematic and dynamic parameters. Direct transitions between controllers are demonstrated as well as parameterized control of changes in direction and speed. Feedback-error learning is applied to learn predictive torque models, which allows for the low-gain control that typifies many natural motions as well as producing smoother simulated motion.

REFERENCES

• 1: Joel Auslander , Alex Fukunaga , Hadi Partovi , Jon Christensen , Lloyd Hsu , Peter Reiss , Andrew Shuman , Joe Marks , J. Thomas Ngo, Further experience with controller-based automatic motion synthesis for articulated figures, ACM Transactions on Graphics (TOG), v.14 n.4, p.311-336, Oct. 1995 [doi>10.1145/225294.225295]
• 2: Dasgupta, A., and Nakamura, Y. 1999. Making feasible walking motion of humanoid robots from human motion capture data. In Robotics and Automation, vol. 2, 1044--1049.
• 3: Petros Faloutsos , Michiel van de Panne , Demetri Terzopoulos, Composable controllers for physics-based character animation, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.251-260, August 2001 [doi>10.1145/383259.383287]
• 4: Jessica K. Hodgins , Nancy S. Pollard, Adapting simulated behaviors for new characters, Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.153-162, August 1997 [doi>10.1145/258734.258822]
• 5: Jessica K. Hodgins , Wayne L. Wooten , David C. Brogan , James F. O'Brien, Animating human athletics, Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, p.71-78, September 1995 [doi>10.1145/218380.218414]
• 6: Hodgins, J. K. 1991. Biped gait transitions. In Proceedings of the IEEE International Conference on Robotics and Automation.
• 7: Honda Motor Co., L., 2006. Studies of leg/foot functions of the robot, http://world.honda.com/asimo/p3/technology/.
• 8: Kaneko, K., Kanehiro, F., Kajita, S., Yokoyama, K., Akachi, K., Kawasaki, T., Ota, S., and Isozumi, T. 2002. Design of prototype humanoid robotics platform for HRP. IEEE/RSJ Intl. Conf. on Intell. Robots and Systems.
• 9: Kawato, M., Furukawa, K., and Suzuki, R. 1987. A hierarchical neural-network model for control and learning of voluntary movement. Biological Cybernetics 57, 3, 169--185.
• 10: Kim, J., Park, I., and Oh, J. 2006. Experimental realization of dynamic walking of the biped humanoid robot KHR-2 using zero moment point feedback and inertial measurement. Advanced Robotics 20, 6, 707--736.
• 11: Daniel E. Koditschek , Martin Bühler, Analysis of a simplified hopping robot, International Journal of Robotics Research, v.10 n.6, p.587-605, Dec. 1991 [doi>10.1177/027836499101000601]
• 12: Kudoh, S., Komura, T., and Ikeuchi, K. 2006. Stepping motion for a humanlike character to maintain balance against large perturbations. In Proc. of Intl Conf. on Robotics and Automation, 2661--2666.
• 13: Kuo, A. 1999. Stabilization of Lateral Motion in Passive Dynamic Walking. Intl J. of Robotics Research 18, 9, 917.
• 14: Joseph Laszlo , Michiel van de Panne , Eugene Fiume, Limit cycle control and its application to the animation of balancing and walking, Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, p.155-162, August 1996 [doi>10.1145/237170.237231]
• 15: Miura, H., and Shimoyama, I. 1984. Dynamic Walk of a Biped. Intl J. of Robotics Research 3, 2, 60--74.
• 16: Morimoto, J., Cheng, G., Atkeson, C. G., and Zeglin, G. 2004. A simple reinforcement learning algorithm for biped walking. In Proc. IEEE Int'l Conf. on Robotics and Automation.
• 17: Jun Nakanishi , Stefan Schaal, Feedback error learning and nonlinear adaptive control, Neural Networks, v.17 n.10, p.1453-1465, December 2004 [doi>10.1016/j.neunet.2004.05.003]
• 18: Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., and Kawato, M. 2003. Learning from demonstration and adaptation of biped locomotion with dynamical movement primitives. In Workshop on Robot Learning by Demonstration, IEEE Int'l Conf. Intelligent Robots and Systems.
• 19: NaturalMotion, 2006. http://www.naturalmotion.com.
• 20: ODE. Open dynamics engine. http://www.ode.org.
• 21: Zoran Popović , Andrew Witkin, Physically based motion transformation, Proceedings of the 26th annual conference on Computer graphics and interactive techniques, p.11-20, July 1999 [doi>10.1145/311535.311536]
• 22: Marc H. Raibert , Jessica K. Hodgins, Animation of dynamic legged locomotion, Proceedings of the 18th annual conference on Computer graphics and interactive techniques, p.349-358, July 1991
• 23: Marc H. Raibert, Legged robots that balance, Massachusetts Institute of Technology, Cambridge, MA, 1986
• 24: Sharon, D., and van de Panne, M. 2005. Synthesis of controllers for stylized planar bipedal walking. In International Conference on Robotics and Automation.
• 25: Smith, R. 1998. Intelligent Motion Control with an Artificial Cerebellum. PhD thesis, University of Auckland.
• 26: Kwang Won Sok , Manmyung Kim , Jehee Lee, Simulating biped behaviors from human motion data, ACM SIGGRAPH 2007 papers, August 05-09, 2007, San Diego, California
• 27: Taga, G., Yamaguchi, Y., and Shimizu, H. 1991. Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment. Biological Cybernetics 65, 147--159.
• 28: Takahashi, C. D., Scheidt, R. A., and Reinkensmeyer, D. J. 2001. Impedance Control and Internal Model Formation When Reaching in a Randomly Varying Dynamical Environment. J. Neurophysiology 86 (Aug).
• 29: Tedrake, R., Zhang, T. W., and Seung, H. S. 2004. Stochastic policy gradient reinforcement learning on a simple 3d biped. In IEEE Intl Conf. on Intelligent Robots and Systems.
• 30: Vakakis, A., and Burdick, J. 1990. Chaotic motions in the dynamics of a hopping robot. Proc. IEEE Intl Conf on Robotics and Automation, 1464--1469.
• 31: Michiel van de Panne , Eugene Fiume, Sensor-actuator networks, Proceedings of the 20th annual conference on Computer graphics and interactive techniques, p.335-342, August 02-06, 1993, Anaheim, CA [doi>10.1145/166117.166159]
• 32: van de Panne, M., Kim, R., and Fiume, E. 1994. Virtual wind-up toys for animation. In Graphics Interface, 208--215.
• 33: Vukobratovic, M., and Juricic, D. 1969. Contribution to the synthesis of biped gait. In IEEE Transactions on Biomedical Engineering, vol. 16. 1--6.
• 34: Wayne Lewis Wooten , Jessica K. Hodgins, Simulation of leaping, tumbling, landing, and balancing humans, Georgia Institute of Technology, Atlanta, GA, 1998
• 35: Pawel Wrotek , Odest Chadwicke Jenkins , Morgan McGuire, Dynamo: dynamic, data-driven character control with adjustable balance, Proceedings of the 2006 ACM SIGGRAPH symposium on Videogames, p.61-70, July 30-31, 2006, Boston, Massachusetts [doi>10.1145/1183316.1183325]
• 36: KangKang Yin , Michael B. Cline , Dinesh K. Pai, Motion Perturbation Based on Simple Neuromotor Control Models, Proceedings of the 11th Pacific Conference on Computer Graphics and Applications, p.445, October 08-10, 2003
• 37: Victor Brian Zordan , Jessica K. Hodgins, Motion capture-driven simulations that hit and react, Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation, July 21-22, 2002, San Antonio, Texas [doi>10.1145/545261.545276]
• 38: Victor Brian Zordan , Anna Majkowska , Bill Chiu , Matthew Fast, Dynamic response for motion capture animation, ACM SIGGRAPH 2005 Papers, July 31-August 04, 2005, Los Angeles, California

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.7 Three-Dimensional Graphics and Realism

Additional Classification:
  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY
      F.2.2 Nonnumerical Algorithms and Problems

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Control theory
      I.2.9 Robotics
          Subjects: Kinematics and dynamics
  I.3 COMPUTER GRAPHICS
      I.3.5 Computational Geometry and Object Modeling
          Subjects: Physically based modeling

General Terms:
Algorithms, Design