mees/hulc2
[ICRA2023] Grounding Language with Visual Affordances over Unstructured Data
This project helps robotics engineers train robots to understand and perform complex tasks using natural language instructions. It takes in large datasets of robot interaction, including visual data and some language annotations, and outputs a trained robot policy capable of executing multi-step commands in real-world scenarios. Robotics researchers and developers who are building intelligent robotic systems would find this useful.
No commits in the last 6 months.
Use this if you need to efficiently train a robotic arm to follow abstract, multi-step natural language commands, especially with limited language-annotated data.
Not ideal if your robot tasks are simple, repetitive, or don't require high-level language understanding and generalization.
Stars
45
Forks
4
Language
Python
License
MIT
Category
Last pushed
Oct 29, 2023
Commits (30d)
0
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