A framework for motion planning of digital humans using discrete mechanics and optimal control
Paper in proceedings, 2017

In this paper we present a framework for digital human modelling using discrete mechanics and optimal control. Discrete mechanics is particularly well suited for modelling the dynamics of constrained mechanical systems, which is almost always the case when considering complex human models interacting with the environment. We demonstrate that, by using recently developed recursive dynamics algorithms, we are able to efficiently use discrete mechanics in direct optimal control methods to plan for complex motions. Besides a proper mechanical model, an appropriate objective function is paramount to achieve realistic motions as a solution to an optimal control problem. Hence, several different objective functions, such as for example minimum time or minimum applied torque over the joints, are compared, and the resulting motions are analyzed and evaluated. To further improve the model, we include basic muscular models for the muscles of the shoulder, arm and wrist, and examine how this affects the motions.

discrete mechanics

Optimal control

human motion planning

Author

Staffan C Björkenstam

Chalmers, Signals and Systems, Systems and control, Automation

Johan Nyström

Michael Roller

Joachim Linn

Dan Högberg

Sigrid Leyendecker

Proceedings of the 5th International Digital Human Modeling Symposium

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Control Engineering

Areas of Advance

Production

More information

Created

1/19/2018