  This paper focuses on robustness to disturbance forces and uncertain
payloads. We present a novel formulation to optimize the robustness of dynamic
trajectories. A straightforward transcription of this formulation into a
nonlinear programming problem is not tractable for state-of-the-art solvers,
but it is possible to overcome this complication by exploiting the structure
induced by the kinematics of the robot. The non-trivial transcription proposed
allows trajectory optimization frameworks to converge to highly robust dynamic
solutions. We demonstrate the results of our approach using a quadruped robot
equipped with a manipulator.
