Dobb·E
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About
Dobb·E is an open-source, general-purpose framework for learning robotic manipulation in household settings. It achieves an 81% success rate across 109 tasks in 10 NYC homes. A key innovation is 'The Stick,' a low-cost demonstration collection tool using readily available parts and iPhones. Dobb·E leverages Home Pretrained Representations (HPR), a ResNet-34 model trained on data collected with The Stick. The project addresses challenges unique to home robotics, such as variable lighting and demonstration quality. The software stack, models, data, and hardware designs are open-sourced to accelerate research in home robotics.
Platform
Keywords
Task
Features
• open-source
• home pretrained representations (hpr) model
• demonstration collection tool ('the stick')
• 20 minutes to learn a new task
• 81% success rate
• 10 nyc homes
• 109 tasks
• general framework for learning household robotic manipulation
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