Dobb·E

Dobb·E

Empowering Homes with Versatile Robotic Assistance

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Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a generalist machine for homes that can adapt and learn from users' needs efficiently. Dobb·E can learn a new task with just five minutes of demonstration, achieving an 81% success rate in various household environments. The project focuses on accelerating research on home robots and making robot assistants a common sight in every home.

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Features

Advantages

  • Cost-effective and affordable solution for household robotic manipulation
  • Quick learning curve with only five minutes of demonstration
  • High success rate of 81% in various household tasks
  • Open-source software stack and models for research and development
  • Addresses real-world challenges in home robotics

Disadvantages

  • Dependence on demonstration quality by non-expert users
  • Limited to household manipulation tasks
  • Requires adaptation time for the Home Pretrained Representations (HPR) model

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