Dobb-E
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Open-source research framework for teaching home robots new manipulation tasks from a few minutes of demonstration.
What it does
Dobb-E is an open-source, general-purpose framework for learning household robotic manipulation, developed by researchers at NYU and collaborators. Using a cheap iPhone-based demonstration tool called The Stick, it collects home demonstrations and trains Home Pretrained Representations, letting a mobile robot learn a new task from about five minutes of demonstration. It reports an 81% success rate across 109 tasks in 10 NYC homes.
Core features
Learns new tasks from ~5 minutes of demonstration
'The Stick' low-cost iPhone demonstration tool
Home Pretrained Representations (HPR) models
Runs on the commercially available Stretch robot
Fully open-source software, data, models and hardware
Best for
→Research into home/household robot manipulation
→Rapidly teaching robots new tasks by demonstration
→Benchmarking imitation learning in real homes