  Dynamic motions of humans and robots are widely driven by posture-dependent
nonlinear interactions between their degrees of freedom. However, these
dynamical effects remain mostly overlooked when studying the mechanisms of
human movement generation. Inspired by recent works, we hypothesize that human
motions are planned as sequences of geodesic synergies, and thus correspond to
coordinated joint movements achieved with piecewise minimum energy. The
underlying computational model is built on Riemannian geometry to account for
the inertial characteristics of the body. Through the analysis of various human
arm motions, we find that our model segments motions into geodesic synergies,
and successfully predicts observed arm postures, hand trajectories, as well as
their respective velocity profiles. Moreover, we show that our analysis can
further be exploited to transfer arm motions to robots by reproducing
individual human synergies as geodesic paths in the robot configuration space.
