metadata
license: cc-by-nc-sa-4.0
IROS-2025-Challenge-Manip
Dataset Summary 📖
This dataset contains the IROS Challenge - Manipulation Track benchmark, organized into pretrain, train, and validation splits.
- Pretrain split: ~20,000 single pick-and-place trajectories, packaged into tar files (each containing ~1,000 trajectories).
- Train split: task-specific demonstrations, with ~100 trajectories provided per task.
- Validation split: includes the test-time scenes and object assets in USD format.
Each trajectory in the pretrain and train splits contains:
- Multi-view video recordings (three perspectives: head-mounted camera and two wrist cameras)
- Robot states (joint positions, gripper states, etc.)
- Actions corresponding to the task execution
This dataset is designed to support pretraining, task-specific fine-tuning, and evaluation for robotic manipulation in the IROS Challenge setting.
Get started 🔥
Download the Dataset
To download the full dataset, you can use the following code. If you encounter any issues, please refer to the official Hugging Face documentation.
from huggingface_hub import snapshot_download
dataset_path = snapshot_download("InternRobotics/IROS-2025-Challenge-Manip", repo_type="dataset")
Please execute this Python file to post-process the validation set.
cd IROS-2025-Challenge-Manip
python dataset_post_processing.py validation
Unzip the pretrain dataset
cd pretrain
for i in {1..20}; do
echo "Extracting $i.tar.gz ..."
tar -xzf "$i.tar.gz"
done
Dataset Structure
pretrain Folder hierarchy
pretrain
├── 1.tar.gz
│ └── 1/
│ ├── data/
│ ├── meta/
│ └── videos/
├── 2.tar.gz
│ └── 2/
│ ├── data/
│ ├── meta/
│ └── videos/
...
├── 20.tar.gz
└── 20/
├── data/
├── meta/
└── videos/
train Folder hierarchy
train
├── collect_three_glues
│ ├── data/
│ ├── meta/
│ └── videos/
├── collect_two_alarm_clocks/
├── collect_two_shoes/
├── gather_three_teaboxes/
├── make_sandwich/
├── oil_painting_recognition/
├── organize_colorful_cups/
├── purchase_gift_box/
├── put_drink_on_basket/
└── sort_waste/
validation Folder hierarchy
validation
├── IROS_C_V3_Aloha_seen
│ ├── collect_three_glues
│ │ ├── 000
│ │ │ ├── meta_info.pkl
│ │ │ ├── scene.usd
│ │ │ └── SubUSDs -> ../SubUSDs
│ │ ├── 001/
│ │ ├── 002/
│ │ ├── 003/
│ │ ├── 004/
│ │ ├── 005/
│ │ ├── 006/
│ │ ├── 007/
│ │ ├── 008/
│ │ ├── 009/
│ │ └── SubUSDs
│ │ ├── materials/
│ │ └── textures/
│ ├── collect_two_alarm_clocks/
│ ├── collect_two_shoes/
│ ├── gather_three_teaboxes/
│ ├── make_sandwich/
│ ├── oil_painting_recognition/
│ ├── organize_colorful_cups/
│ ├── purchase_gift_box/
│ ├── put_drink_on_basket/
│ └── sort_waste/
└── IROS_C_V3_Aloha_unseen
├── collect_three_glues/
├── collect_two_alarm_clocks/
├── collect_two_shoes/
├── gather_three_teaboxes/
├── make_sandwich/
├── oil_painting_recognition/
├── organize_colorful_cups/
├── purchase_gift_box/
├── put_drink_on_basket/
└── sort_waste/
License and Citation
All the data and code within this repo are under CC BY-NC-SA 4.0. Please consider citing our project if it helps your research.
@misc{contributors2025internroboticsrepo,
title={IROS-2025-Challenge-Manip Colosseum},
author={IROS-2025-Challenge-Manip Colosseum contributors},
howpublished={\url{https://github.com/internrobotics/IROS-2025-Challenge-Manip}},
year={2025}
}