In recent years, there have been a number of popular robotics competitions whose intent is to advance the state of research by comparing embodied entries against one another in real time. The IEEE Humanoid application challenge is intended to broaden these by allowing more open ended entries, with a general theme within which entrants are challenged to create the most effective application involving a humanoid robot. This year’s theme was Robot Magic, and this paper describes our first-place winning entry in the 2017 competition, running on a ROBOTIS OP2 humanoid robot. We describe the overall agent design and contributions to perception, learning, control, and representation, together supporting a robust live robot magic performance.
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