Dobb·E

towards home robots with an open-source platform. Dobb·E is an open-source framework for teaching robots household tasks via imitation learning in 20 minutes. The framework uses a simple tool called the Stick, collects a dataset called Homes of New York (HoNY) with it, and then trains a representation learning model, Home Pretrained Representations (HPR) with it. Then, Dobb·E uses five minutes of collected data in a new home for a novel task and within fifteen minutes, gives a policy that can solve the task with 81% average success rate. Proud to share our open-source robot platform, Dobb·E, a home robot system that needs just 5 minutes of human teaching to learn new tasks.

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