This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Model Predictive Control for Human Motion Simulation
Technical Paper
2009-01-2306
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
This paper describes a novel model-based controller designed to simulate human motion in dynamic virtual environments. The controller was tested on SantosTM, the digital human developed at the Virtual Soldier Research Program at the University of Iowa.
A planar 3-degrees-of-freedom model of the human arm was used to test the hypothesis. The controller was used to predict on line, optimal torques required to move the end effector towards a target point. The control law was implemented using classical gradient-based optimization and the recently developed technique of model predictive control (MPC). An advantage of MPC is that it replaces intractable closed loop optimization problems with more easily implementable open loop problems.
The controller was used to produce physically consistent simulations of the motion of a human arm in a virtual environment in the presence of external disturbances that were not known in advance.
Recommended Content
Citation
Goussous, F., Bhatt, R., Dasgupta, S., and Abdel-Malek, K., "Model Predictive Control for Human Motion Simulation," SAE Technical Paper 2009-01-2306, 2009, https://doi.org/10.4271/2009-01-2306.Also In
References
- BrudelingA., WilliamsL., “Motion Signal Processing”, Proceedings of SIGGRAPH 1995, ACM SIGGRAPH, pages 97-104, (1995).
- ChalodhornR., GrimesD., MaganisG., RaoR., “Learning Dynamic Humanoid Motion using Predictive Control in Low Dimensional Subspaces”, Proceedings of the 2005 5th IEEE-RAS International Conference on Humanoid Robots, (2005).
- ChevallereauC., Formal'skyA., and PerrinB. Low energy cost reference trajectories for a biped robot, Proceedings of IEEE International Conference on Robotics and Automation, Leuven, Belgium, Computers in Physics, 10(2), 1996, pages 138-143.
- CohenS. and HindmarshA., “CVODE, A Stiff/Nonstiff ODE Solver in C”, Computers in Physics, 10(2), 1996, pages 138-143.
- da SilvaM., AbeY., PopovicJ., “Simulation of Human Motion Data using Short-Horizon Model-Predictive Control”, Computer Graphics Forum, Vol. 27, No. 2, pages 371-380, (2008).
- DenavitJ., and HartenbergR., “ A kinematic notation for lower-pair mechanisms based on matrices. Journal of Applied Mechanic, Vol. 77, pages 215-221 (1955).
- EsfanjaniR., TowhidkhahF., “Application of Nonlinear Model Predictive Controller For FES-Assisted Standing Up in Paraplegia”, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, September 1-4, (2005).
- FaloutsosP., van de PanneM., TerzopoulosD., “Composable Controllers for Physics-Based Character Animation”, Proceedings of the 28th annual conference on computer graphics and interactive techniques, pages 251-260, (2001).
- FangA., PollardN., “Efficient Synthesis of Physically Valid Motion”, Proceedings of SIGGRAPH 2003, ACM Transactions on Graphics Vol. 22, No. 2, pages 417-426, (2003).
- GillP.E., MurrayW., and SaundersM.A. “SNOPT: An SQP algorithm for large-scale constrained optimization”, SIAM J. OPTIM. Vol. 12, pages 979-1006 (2002).
- GleicherM., “Retargeting Motion to New Characters”, Proceedings of SIGGRAPH 1998, ACM SIGGRAPH, pages 33-42, (1998).
- HodginsJ., WootenW., BroganD., O'BrienJ., “Animating Human Athletics”, Proceedings of SIGGRAPH 1995, ACM SIGGRAPH, pages 71-78, (1995).
- KimJ., Abdel-MalekK., YangJ., MarlerT., “Prediction and Analyses of Human Motion Dynamics Performing Different Tasks”, International Journal of Human Factors Modelling and Simulation, Vol. 1, No. 1, (2006).
- McGuanS., “Human Modeling - From Bubblemen to Skeletons”, SAE Digital Human Modeling for Design and Engineering Conference, June 26-28, Arlington, Virginia, (2001).
- PollardN., ZordanV., “Physically Based Grasping Control from Example”, Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on computer animation, pages 59-66, (2005).
- RousselL., Canudas-de-WitC., and GoswamiA. Generation of energy optimal complete gait cycles for biped robots, Proceedings of IEEE International Conference on Robotics and Automation, Leuven, Belgium, 3, p. 2036-2041.
- Virtools by Dassault Systems - www.virtools.com.
- WitkinA., PopovicZ., “Motion Warping”, Proceedings of SIGGRAPH 1995, ACM SIGGRAPH, pages 105-108, (1995).
- XiangY., ChungH.-J., KimJ., BhattR. M., MarlerT., RahmatallaS., YangJ., AroraJ. S., and Abdel-MalekK., “Predictive Dynamics: An Optimization-Based Novel Approach for Human Motion Simulation,” Structural and Multidisciplinary Optimization (in review 2009)
- ZordanV., HodginsJ., “Motion Capture-Driven Simulations that Hit and React”, Proceedings of the 2002 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, ACM press, pages 89-96, (2002).