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About this paper
Liuchuan Yu
VREgo tests whether consumer VR demonstrations can train a robot for tabletop manipulation. It uses PICO stereo and hand tracking, adapting HumanEgo’s representation and policy, and changes training trajectories and execution rules. In simulation, both-placement success rose from 2/100 to 93.8% across four noise seeds, but the same 100 layouts informed rule development and evaluation.
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