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RLinf/dreamzero-franka-pnp

DreamZero Franka Pick-and-Place This dataset contains real-world Franka Panda pick-and-place demonstrations used for DreamZero supervised fine-tuning and real-world deployment in RLinf. Dataset Summary Format: LeRobot v2.1 Robot: Franka Panda Task: Pick up the object and put it into another bin Episodes: 140 Frames: 9,685 FPS: 10 Videos: 280 Image streams: observation.images.image, observation.images.wrist_image Image size: 128 x 128 RGB State: float32, shape… See the full description on the dataset page: https://huggingface.co/datasets/RLinf/dreamzero-franka-pnp.

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DreamZero Franka Pick-and-Place

This dataset contains real-world Franka Panda pick-and-place demonstrations used for DreamZero supervised fine-tuning and real-world deployment in RLinf.

Dataset Summary

  • —Format: LeRobot v2.1
  • —Robot: Franka Panda
  • —Task: Pick up the object and put it into another bin
  • —Episodes: 140
  • —Frames: 9,685
  • —FPS: 10
  • —Videos: 280
  • —Image streams: observation.images.image, observation.images.wrist_image
  • —Image size: 128 x 128 RGB
  • —State: float32, shape [19]
  • —Action: float32, shape [7]

Layout

The repository keeps the standard LeRobot directory layout:

text
meta/
data/
videos/

Important files include:

  • —meta/info.json
  • —meta/tasks.jsonl
  • —meta/stats.json
  • —meta/episodes.jsonl
  • —data/chunk-000/episode_*.parquet
  • —videos/chunk-000/observation.images.image/episode_*.mp4
  • —videos/chunk-000/observation.images.wrist_image/episode_*.mp4

Usage With RLinf

Download the dataset:

bash
huggingface-cli download RLinf/dreamzero-franka-pnp --repo-type dataset --local-dir ./franka_pnp

Generate DreamZero metadata:

bash
python toolkits/lerobot/generate_dreamzero_metadata.py \
  --preset franka_pnp \
  --dataset-root ./franka_pnp \
  --output-metadata ./franka_pnp_metadata.json

Use the dataset with embodiment_tag: franka_pnp. For real-world Franka evaluation in RLinf, use the DreamZero Franka config and keep the gripper action convention aligned with gripper_action_mode: signed.

Safety and Scope

This dataset is intended for research on robot imitation learning and real-world deployment. Any robot execution should be validated in a controlled environment with appropriate hardware safety checks.