Modeling and identification of emotional aspects of locomotion

The studies of emotional facial expressions and emotional body language are currently receiving a lot of attention in the cognitive sciences. In this project, we study implicit bodily expression of emotions during standard motions, such as walking forwards.An underlying assumption of our work is that all human motion is optimal in some sense and that different emotions induce different objective functions, which result in different deformations of normal motion.We created a 3D rigid-body model of a human of which we use the forward dynamics simulation in an optimal control context. We performed two kinds of optimizations: (i) reconstruction of dynamic quantities, such as joint torques, of pre-recorded data of emotional walking motions and (ii) forward optimization that generates neutral and varied walking motions using different objective functions. Optimizations are performed with the software package MUSCOD-II, which uses a direct multiple-shooting discretization scheme. The results of this work form the foundation for further analysis of emotional motions using inverse optimal control methods.

► In this study we investigate of full-body emotional walking motions.
► We use a model based approach using the dynamics simulation of a rigid-body model.
► We use optimal control methods to reconstruct dynamic quantities from mo-cap data.
► We also generate walking motions by optimization using different criteria.
► Results of this work are the base for further analysis using inverse optimal control.