Interactive Language: Talking to Robots in Real Time

@article{Lynch2022InteractiveLT,
  title={Interactive Language: Talking to Robots in Real Time},
  author={Corey Lynch and Ayzaan Wahid and Jonathan Tompson and Tianli Ding and James Betker and Robert K. Baruch and Travis Armstrong and Peter R. Florence},
  journal={ArXiv},
  year={2022},
  volume={abs/2210.06407}
}
—We present a framework for building interactive, real- time, natural language-instructable robots in the real world, and we open source related assets (dataset, environment, benchmark, and policies). Trained with behavioral cloning on a dataset of hundreds of thousands of language-annotated trajectories, a produced policy can proficiently execute an order of magnitude more commands than previous works: specifically we estimate a 93.5% success rate on a set of 87,000 unique natural language… 

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