license: apache-2.0
task_categories:
- robotics
tags:
- manipulation
- vla
Simulated Franka Pick-Cube Tactile Dataset in LeRobot Format
The dataset was generated using the Robot Control Stack (RCS). It is in LeRobot format and thus ready-to-train. The task is a simple "grasp the cuboid". It is created by a hardcoded trajectory planner. It contains tactile images from digit sensors attached to the fingers, rendered by tacto.
RCS is a flexible Gymnasium wrapper-based robot control interface made for robot learning and specifically Vision-Language-Action (VLA) models. It unifies MuJoCo simulation and real world robot control with four supported robots: FR3/Panda, xArm7, UR5e and SO101. It ships with several pre-build apps including data collection via teleoperation and remote model inference.
Project page: https://robotcontrolstack.github.io/ RCS Code: https://github.com/RobotControlStack/robot-control-stack
Dataset Structure
{
"codebase_version": "v3.0",
"robot_type": "fr3",
"total_episodes": 797,
"total_frames": 194468,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:797"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"features": {
"observation.images.image": {
"dtype": "image",
"shape": [
256,
256,
3
],
"names": [
"height",
"width",
"channel"
],
"fps": 30.0
},
"observation.images.image2": {
"dtype": "image",
"shape": [
256,
256,
3
],
"names": [
"height",
"width",
"channel"
],
"fps": 30.0
},
"observation.images.tactile_left": {
"dtype": "image",
"shape": [
320,
240,
3
],
"names": [
"height",
"width",
"channel"
],
"fps": 30.0
},
"observation.images.tactile_right": {
"dtype": "image",
"shape": [
320,
240,
3
],
"names": [
"height",
"width",
"channel"
],
"fps": 30.0
},
"observation.state": {
"dtype": "float32",
"shape": [
15
],
"names": [
"state"
],
"fps": 30.0,
"description": "joints (7) + gripper (0 close, 1 open) (1) + tau_ext (7)"
},
"action": {
"dtype": "float32",
"shape": [
8
],
"names": [
"action"
],
"fps": 30.0
},
"timestamp": {
"dtype": "float32",
"shape": [
1
],
"names": null
},
"frame_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"episode_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"task_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
}
}
}
Citation
If you find this dataset or RCS useful for your work, please consider citing it:
@inproceedings{juelg2025robotcontrolstack,
title={{Robot Control Stack}: {A} Lean Ecosystem for Robot Learning at Scale},
author={Tobias J{\"u}lg and Pierre Krack and Seongjin Bien and Yannik Blei and Khaled Gamal and Ken Nakahara and Johannes Hechtl and Roberto Calandra and Wolfram Burgard and Florian Walter},
year={2025},
booktitle={Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
note={Accepted for publication.}
}