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Trossen Gripper Pick-and-Place Simulation Dataset

Simulated pick-and-place episodes for imitation learning, generated in MuJoCo with a Trossen parallel-jaw gripper on a 3-DOF Cartesian gantry.

Dataset Summary

Episodes 500
Steps per episode 145
Record frequency 20 Hz
Simulator MuJoCo (timestep: 1ms)
Task Randomized cube pick-and-place
Success rate ~100% (placement error < 20mm)

Task Description

A parallel-jaw gripper mounted on a 3-DOF (x, y, z) Cartesian gantry picks up a 2cm cube (30g) from a randomized position on a table and places it at a randomized target location. Each episode follows a 13-point waypoint trajectory with smooth interpolation.

File Structure

episodes/
  episode_0000.h5 ... episode_0499.h5
videos/
  wrist_cam_0000.mp4 ... wrist_cam_0499.mp4

HDF5 Episode Format

Each episode_NNNN.h5 contains:

Key Shape Dtype Description
actions/ee_pose (145, 7) float32 Target end-effector pose [x, y, z, qw, qx, qy, qz]
actions/gripper (145, 1) float32 Gripper command (0.0 = open, 1.0 = closed)
observations/ee_pose (145, 7) float32 Actual end-effector pose [x, y, z, qw, qx, qy, qz]
observations/gripper_width (145, 1) float32 Gripper opening in meters (0 - 0.088m)
observations/timestamp (145,) float64 Seconds since episode start
videos/wrist_cam (145,) int64 Frame indices into companion MP4
env_state scalar JSON Episode metadata (pick/place positions, placement error)
success scalar bool True if placement error < 20mm
episode_length scalar int64 Number of timesteps (145)

Conventions

Convention Value
Action frame World (absolute)
Observation frame World (absolute)
Quaternion format wxyz (constant, no rotation DOF)
Gripper action 0 = open, 1 = closed

Simulation Parameters

Parameter Value
Gantry workspace X: ±0.25m, Y: ±0.15m, Z: -0.4m to 0m
Gripper stroke 0 - 88mm
Cube size 2cm, 30g
Gantry Kp 5000
Gripper Kp 500

Usage

import h5py

with h5py.File("episodes/episode_0000.h5", "r") as ep:
    actions = ep["actions/ee_pose"][:]       # (145, 7)
    gripper = ep["actions/gripper"][:]       # (145, 1)
    obs_pose = ep["observations/ee_pose"][:] # (145, 7)
    success = ep["success"][()]              # bool

Citation

If you use this dataset, please cite this repository.

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