  An innovative approach of gaining insight into motor skills involved in human
body flight is proposed. The key idea is the creation of a model autonomous
system capable of virtually performing skydiving maneuvers. A dynamic skydiver
model and simulator is developed, comprising biomechanical, aerodynamic, and
kinematic models, dynamic equations of motion, and a virtual reality
environment. Limb relative orientations, and resulting inertial body angular
position and velocity are measured in skydiving experiments in a vertical wind
tunnel and in free fall. These experimental data are compared with
corresponding simulation data to tune and verify the model for basic skydiving
maneuvers. The model is further extended to reconstruct advanced aerial
maneuvers, such as transitions between stable equilibria. The experimental data
are used to estimate skydiver's conscious inputs as a function of time, via an
Unscented Kalman Filter modified for this purpose.
