A Novel Model-Based Predictive Controller for Human Motion Simulation in Dynamic Environments

Document Number: 2009-01-2306

Date Published: June 2009

Author(s):
Faisal Goussous - Univ. of Iowa
Karim Abdel-Malek - Univ of Iowa
Rajankumar Bhatt - Univ of Iowa
Soura DASGUPTA - Univ. of Iowa

Abstract:
This paper describes a novel model-based controller designed to simulate human motion in dynamic virtual environments. The controller was tested on Santos\sT, 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.

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See other papers presented at Digital Human Modeling for Design and Engineering Conference and Exhibition, June 2009, Gothenburg, SWEDE, Session: Biomechanics

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