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Advanced motor skills are essential for robots to physically coexist withhumans. Much research on robot dynamics and control has achieved success onhyper robot motor capabilities, but mostly through heavily case-specificengineering. Meanwhile, in terms of robot acquiring skills in a ubiquitousmanner, robot learning from human demonstration (LfD) has achieved greatprogress, but still has limitations handling dynamic skills and compoundactions. In this paper, we present a composite learning scheme which goesbeyond LfD and integrates robot learning from human definition, demonstration,and evaluation. The method tackles advanced motor skills that require dynamictime-critical maneuver, complex contact control, and handling partly softpartly rigid objects. We also introduce the "nunchaku flipping challenge", anextreme test that puts hard requirements to all these three aspects. Continuedfrom our previous presentations, this paper introduces the latest update of thecomposite learning scheme and the physical success of the nunchaku flippingchallenge.

Robot Composite Learning and the Nunchaku Flipping Challenge