VVVVVVVVIC/glam-datasets
GLAM Datasets Heterogeneous manipulation demonstrations for GLAM: Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models (project page · code). Each task combines a small target set — action-labelled demonstrations on our dual-arm Kinova robot (Frank) in MuJoCo — with a larger, action-free auxiliary set collected by a floating UMI gripper, also in MuJoCo. Contents Archive Task Episodes Size stack_two.tar task 1 — stack two… See the full description on the dataset page: https://huggingface.co/datasets/VVVVVVVVIC/glam-datasets.
GLAM Datasets
Heterogeneous manipulation demonstrations for GLAM: Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models (project page · code).
Each task combines a small target set — action-labelled demonstrations on our dual-arm Kinova robot (Frank) in MuJoCo — with a larger, action-free auxiliary set collected by a floating UMI gripper, also in MuJoCo.
Contents
Each episode folder contains the trajectory (*.npz: poses, joints, actions), raw RGB frames from two cameras (front_frames/, overhead_frames/), and the corresponding object masks (*_frames_mask/).
Usage
pip install -U huggingface_hub
hf download VVVVVVVVIC/glam-datasets --repo-type dataset --local-dir data/
tar -xf data/stack_two.tar -C data/ && rm data/stack_two.tar
tar -xf data/stack_three.tar -C data/ && rm data/stack_three.tarThis produces data/stack_two/{umi,frank}/task_01/... and data/stack_three/{umi,frank}/task_02/..., ready for the training commands in the GLAM repository.
Citation
@article{wang2026imitation,
title={Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models},
author={Wang, Tianyou and Lei, Anson and Watson, Joe and Posner, Ingmar},
journal={arXiv preprint arXiv:2606.21672},
year={2026}
}