GVLA/MiGA-Dataset

MiGA: Multi-gripper dataset for Gripper-aware Vision-Language-Action models

Companion dataset for GVLA (Gripper-aware Vision-Language-Action Models), submitted to ECCV 2026 (paper #5218).

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Overview of MiGA

MiGA is a large-scale multi-gripper-aware dataset featuring diverse gripper types on complex tasks, explicitly capturing how the same task requires different strategies depending on the gripper morphology.

• Format: LeRobot dataset schema, stored as Parquet
• Domains: real-world + simulation
• Modalities: third-person RGB (image), wrist-camera RGB (wrist_image), robot state (pose + gripper opening, 8-dim), actions (delta pose + gripper command, 7-dim), per-episode/task indices
• License: Apache 2.0

Composition of MiGA

MiGA is released as multiple gripper/domain-specific subsets under the GVLA organization on Hugging Face, spanning three robot arms (Franka Panda, UR5, UR10) and five gripper types (parallel-jaw, vacuum/suction, 3-finger, Inspire dexterous hand). Subsets are grouped below by domain (real-world vs. simulation).

Real-world subsets

Gripper type	Gripper config	Robot platform	Episodes	Format	HF dataset repo
Parallel-jaw	Franka panda hand	Franka Panda	1877	Parquet (LeRobot)	GVLA/Franka_panda_parallel_hand_real
Vacuum	Cobot Pump	Franka + Cobot	671	Parquet (LeRobot)	GVLA/Franka_cobot_vacuum_real
Dexterous hand	Inspire dexterous hand	Franka + Inspire Hand	899	Parquet (LeRobot)	GVLA/Franka_inspire_hand_real
Parallel-jaw	Robotiq 85 parallel-jaw	UR5	106	Parquet (LeRobot)	GVLA/UR5_robotiq_85_parallel_real
3 finger	Robotiq 3-f	UR5	-	Parquet (LeRobot)	GVLA/UR5_robotiq_3f_3finger_real

Simulation subsets

Gripper type	Gripper config	Robot platform	Episodes	Format	HF dataset repo
Parallel-jaw	Franka panda hand	Franka Panda	-	Parquet (LeRobot)	GVLA/Franka_panda_parallel_hand_sim
Parallel-jaw	Robotiq 85 parallel-jaw	Franka Panda	4065	Parquet (LeRobot)	GVLA/Franka_robotiq_85_parallel_sim
Vacuum	Cobot	Franka Panda	4829	Parquet (LeRobot)	GVLA/Franka_cobot_vacuum_sim
Vacuum	Short-cup vacuum	Franka Panda	-	Parquet (LeRobot)	GVLA/Franka_short_cup_vacuum_sim
Vacuum	Short-cup vacuum	UR10	2949	Parquet (LeRobot)	GVLA/UR10_short_cup_vacuum_sim

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Data description

Each subset follows the standard LeRobot dataset layout (Parquet data files + meta/info.json), auto-converted by Hugging Face into a browsable Parquet dataset:

GVLA/<gripper_config_repo>/
|-- data/
|   `-- train-*.parquet        # episodes concatenated, indexed by episode_index/frame_index
|-- videos/                    # camera MP4s (if published separately from the parquet)
|-- meta/
|   `-- info.json              # robot type, fps, feature schema

Per-frame fields (confirmed from the live dataset viewer)

Field	Type	Description
image	image (224×224)	Third-person RGB frame
wrist_image	image (224×224)	Wrist-camera RGB frame
state	float32[8]	End-effector pose (xyz + rotation) + gripper opening (2 values)
actions	float32[7]	Delta end-effector action + gripper command
gripper_id	int32	Identifies which gripper config generated this episode (e.g. 0 = parallel-jaw sim, 2 = parallel-jaw real)
timestamp	float32	Time within episode (s)
frame_index	int64	Frame index within episode
episode_index	int64	Episode index within subset
index	int64	Global row index
task_index	int64	Task identifier

File format

All subsets use the Hugging Face LeRobot dataset convention (Parquet + meta/info.json), so they can be loaded either with 🤗 datasets or directly with lerobot's LeRobotDataset loader.

Example of data usage

from datasets import load_dataset

# Load one gripper-config subset directly
ds = load_dataset("GVLA/Franka_panda_parallel_hand_real", split="train")
print(ds[0]["gripper_id"], ds[0]["state"], ds[0]["actions"])

# Or with the LeRobot dataset loader (recommended for training)
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("GVLA/Franka_panda_parallel_hand_real")

To combine subsets for cross-gripper training, concatenate on the shared state/actions/gripper_id schema and use gripper_id to condition or stratify by embodiment.

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Version update

Version 1.0

Initial release across seven gripper/domain subsets: Franka parallel-jaw (sim + real), Franka+Cobot vacuum (real), Franka+Inspire hand (real), UR5+Robotiq 85 parallel-jaw (real), UR5+Robotiq 3-finger (real), and UR10+short-cup vacuum (sim).

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Citation

If you find MiGA useful in your research, please cite:

@inproceedings{zhang2026gvla,
  title     = {Gripper-aware Vision Language Action Models},
  author    = {Zhang, Hanyi and [FILL IN: remaining co-authors]},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2026},
  eprint    = {2608.24603},
  archivePrefix = {arXiv}
}

Paper: arxiv.org/html/2608.24603v1

Reference

• Organization: huggingface.co/GVLA
• Project page: [FILL IN if different from GVLA org page]

Contact / Discussions

For questions or issues, please open a Discussion on any of the dataset repos above, or contact [FILL IN: email].