Forward models for physiological motor control
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Sync: The Emerging Science of Spontaneous Order
Sync: The Emerging Science of Spontaneous Order
MOSAIC Model for Sensorimotor Learning and Control
Neural Computation
Sensorless stabilization of bounce juggling
IEEE Transactions on Robotics
Rhythmic Feedback Control of a Blind Planar Juggler
IEEE Transactions on Robotics
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At the crossing between motor control neuroscience and robotics system theory, the paper presents a rhythmic experiment that is amenable both to handy laboratory implementation and simple mathematical modeling. The experiment is based on an impact juggling task, requiring the coordination of two upper-limb effectors and some phase-locking with the trajectories of one or several juggled objects. We describe the experiment, its implementation and the mathematical model used for the analysis. Our underlying research focuses on the role of sensory feedback in rhythmic tasks. In a robotic implementation of our experiment, we study the minimum feedback that is required to achieve robust control. A limited source of feedback, measuring only the impact times, is shown to give promising results. A second field of investigation concerns the human behavior in the same impact juggling task. We study how a variation of the tempo induces a transition between two distinct control strategies with different sensory feedback requirements. Analogies and differences between the robotic and human behaviors are obviously of high relevance in such a flexible setup.