UT-Austin-RPL/TRILL
Official codebase for TRILL (Teleoperation and Imitation Learning for Loco-manipulation)
This project helps robotics researchers and engineers teach complex movement and manipulation skills to humanoid robots. You provide human demonstrations using a VR interface, and the system translates your actions into robot movements. The output is a learned policy that allows the humanoid robot to perform intricate tasks autonomously.
124 stars. No commits in the last 6 months.
Use this if you need an efficient way to train humanoid robots for tasks requiring both walking and precise object handling without extensive manual programming.
Not ideal if you are working with non-humanoid robots or if you do not have access to VR for demonstration data collection.
Stars
124
Forks
13
Language
Python
License
MIT
Category
Last pushed
Aug 07, 2025
Commits (30d)
0
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