  Complex motions for robots are frequently generated by switching among a
collection of individual movement primitives. We use this approach to formulate
robot motion plans as sequences of primitives to be executed one after the
other. When dealing with dynamical movement primitives, besides accomplishing
the high-level objective, planners must also reason about the effect of the
plan's execution on the safety of the platform. This task becomes more daunting
in the presence of disturbances, such as external forces. To alleviate this
issue, we present a framework that builds on rigorous control-theoretic tools
to generate safely-executable motion plans for externally excited robotic
systems. Our framework is illustrated on a 3D limit-cycle gait bipedal robot
that adapts its walking pattern to persistent external forcing.
