charithmunasinghe/piper_picking_tests

PiPER Robot Teaching Episodes Dataset

13 teleoperation demonstrations for robot manipulation using a 7-DOF PiPER arm. Fully compatible with LeRobot v3 format.

Quick Info

• Episodes: 13 | Tasks: 12 | Size: ~6.2 GB | FPS: 30
• Robot: PiPER 7-DOF arm | Cameras: Table (800×720) + Wrist | Version: v0.3
• Format: HDF5 + PNG images | Compatible: LeRobot v3, ACT, Diffusion Policy, SmolVLA

Tasks

cleaningcloth fillamentroll gamecontroller hexwrench pencil scissors scissors_hidden screwdriver smallkey smallpaper smallwoodenstick thinmetaldisk

Dataset Structure

{episode_name}_{timestamp}.hdf5          # Robot state, actions, compressed images
{episode_name}_{timestamp}.json          # Episode metadata (frames, fps, stats)
{episode_name}_images/
  ├── observation.images.table_cam/      # 800×720 PNG frames
  └── observation.images.wrist_cam/      # PNG frames (vertically flipped)
meta_data/
  ├── info.json                          # Dataset config, encoding, shapes
  ├── tasks.jsonl                        # Task definitions
  └── episodes.jsonl                     # Episode-task mapping
info.json                                # Root metadata (LeRobot v3)

HDF5 Structure

• observations/state: 7-DOF joint angles (degrees)
• observations/images/table_cam: Compressed JPEG images
• observations/images/wrist_cam: Compressed JPEG images
• actions: 7-DOF commands
• timestamps: Frame timestamps

Metadata (JSON)

Each episode JSON contains: episode_name, n_frames, duration_seconds, fps, state_dim, cameras, state_stats (mean/std/min/max), recording_date

Usage

LeRobot Library (Recommended)

from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("charithmunasinghe/piper_picking_tests", version="v0.3")

for batch in dataset:
    state = batch['observation']['observation.state']
    action = batch['action']
    table_img = batch['observation']['observation.images.table_cam']
    wrist_img = batch['observation']['observation.images.wrist_cam']

Visualize

from lerobot.scripts.visualize_dataset import visualize_dataset

visualize_dataset(
    repo_id="charithmunasinghe/piper_picking_tests",
    episode_index=0,
    version="v0.3"
)

Direct HDF5 Access

import h5py
from PIL import Image
from pathlib import Path

with h5py.File("screwdriver_20251104_203022.hdf5", 'r') as f:
    states = f['observations/state'][:]
    actions = f['actions'][:]

img = Image.open("screwdriver_images/observation.images.table_cam/frame_000000.png")

Dataset Info

• Collection: Human teleoperation in lab environment
• Preprocessing: Table camera cropped (+300,0 offset), wrist camera flipped vertically
• Split: Single train split (13 episodes)
• License: MIT

Citation

@dataset{piper_teaching_episodes_2025,
  title={PiPER Robot Teaching Episodes Dataset},
  author={Munasinghe, Charith and Toffetti, Giovanni},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/charithmunasinghe/piper_picking_tests}}
}

Contact: charithmunasinghe (Hugging Face)