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

Safe Adaptive Switching among Dynamical Movement Primitives: Application to 3D Limit-Cycle Walkers