A bilevel optimization approach to obtain optimal cost functions for human arm movements

Abstract

Using a bilevel optimization approach, we investigate the question how humansplan and execute their arm motions.It is known that human motions are (approximately) optimal for suitable andunknown cost functions subject to the dynamics. We investigate the followinginverse problem: Which cost function out of a parameterized family (e.g.,convex combinations of functions suggested in the literature) reproducesrecorded human arm movements best? The lower level problem is an optimalcontrol problem governed by a nonlinear model of the human arm dynamics.The approach is analyzed for a dynamical 3D model of the human arm.Furthermore, results for a two-dimensional experiment with human probandsare presented.