Code for the paper GHIL-Glue: Hierarchical Control with Filtered Subgoal Images.
This repository contains the code for evaluating GHIL-Glue with both image-generative and video-generative high-level policies, and implements our subgoal filtering method.
The code for training the image-generative high-level policies can be found in the original SuSIE repo. We use the same checkpoints for the image-generative high-level policies that are used in SuSIE. The code for training the video-generative high level policies can be found in our fork of the DynamiCrafter repo. The code for training the low-level policies and the subgoal classifier networks can be found in our fork of the BridgeData V2 repo. All checkpoints can be downloaded from https://huggingface.co/kyle-hatch-tri/ghil-glue-checkpoints.
git clone --recurse-submodules https://github.com/kyle-hatch-tri/ghil-glue.git
conda create -n ghil-glue python=3.8
- Install tensorflow and JAX
bash install.sh
(for troubleshooting see https://github.com/mees/calvin)
To evaluate GHIL-Glue on the CALVIN simulator benchmark,
- Set the values of the environment variables in
eval_ghilglue.sh
to the paths to your downloaded checkpoints. - Run
bash eval_ghilglue.sh
To evaluate GHIL-Glue on a physical BridgeData V2 WidowX environment,
- Set up your WidowX server following these instructions from the BridgeData V2 repo.
- Convert the low-level policy checkpoints to hlo format using
external/susie/scripts/policy_ckpt_to_hlo.py
- Set the values of the environment variables in
external/susie/scripts/robot/eval_diffusion.sh
to the paths to your downloaded checkpoints. - Run
bash external/susie/scripts/robot/eval_diffusion.sh
This code is based on calvin-sim from Pranav Atreya.
If you use this code and/or GHIL-Glue in your work, please cite the paper with:
@misc{hatch2024ghilgluehierarchicalcontrolfiltered,
title={GHIL-Glue: Hierarchical Control with Filtered Subgoal Images},
author={Kyle B. Hatch and Ashwin Balakrishna and Oier Mees and Suraj Nair and Seohong Park and Blake Wulfe and Masha Itkina and Benjamin Eysenbach and Sergey Levine and Thomas Kollar and Benjamin Burchfiel},
year={2024},
eprint={2410.20018},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2410.20018},
}