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---
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license: apache-2.0
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library_name: lerobot
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tags:
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- robotics
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- imitation-learning
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- aloha
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- act
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- lerobot
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datasets:
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- lerobot/aloha_sim_transfer_cube_human_image
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pipeline_tag: robotics
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---
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# ACT Model for ALOHA TransferCube Task
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A lightweight Action Chunking with Transformers (ACT) model trained on the ALOHA simulation TransferCube task.
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## Model Description
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| Property | Value |
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|----------|-------|
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| Architecture | ACT (Action Chunking with Transformers) |
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| Parameters | 52M |
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| Task | ALOHA TransferCube-v0 |
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| Training Steps | 60,000 |
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| Batch Size | 32 |
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| Success Rate | ~42% |
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## Training Data
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- **Dataset**: [lerobot/aloha_sim_transfer_cube_human_image](https://huggingface.co/datasets/lerobot/aloha_sim_transfer_cube_human_image)
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- **Episodes**: 50 human demonstrations
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- **Frames**: 20,000
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## Task Description
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The TransferCube task requires a bimanual robot to:
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1. Pick up a red cube with the right arm
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2. Transfer the cube to the left gripper
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## Demo Video
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<video controls src="eval_episode_3.mp4" title="TransferCube Demo"></video>
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## Training Environment
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- **GPU**: RTX A6000
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- **Framework**: LeRobot 0.4.3
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- **Training Time**: Around 11.5 hours
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## Usage
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### Installation
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```bash
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pip install lerobot gym-aloha
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```
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### Training
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```bash
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lerobot-train \
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--policy.type=act \
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--dataset.repo_id=lerobot/aloha_sim_transfer_cube_human_image \
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--env.type=aloha \
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--env.task=AlohaTransferCube-v0 \
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--batch_size=32 \
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--steps=60000 \
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--eval_freq=5000 \
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--output_dir=./outputs/act_aloha_cube_best \
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--wandb.enable=false \
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--policy.push_to_hub=false
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```
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### Evaluation
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```bash
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lerobot-eval \
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--policy.path=LeTau/act_aloha_transfer_cube \
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--env.type=aloha \
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--env.task=AlohaTransferCube-v0 \
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--eval.batch_size=1 \
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--eval.n_episodes=20
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```
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### Fine-tuning
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```bash
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lerobot-train \
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--resume=true \
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--config_path=LeTau/act_aloha_transfer_cube/train_config.json \
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--steps=100000
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```
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## Results
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| Evaluation | Episodes | Success Rate | Avg Sum Reward |
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|------------|----------|--------------|----------------|
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| Training | 50 | 42% | 116.26 |
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| Independent | 20 | 35% | 95.95 |
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**Expected success rate: 35-42%**
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## Detailed Evaluation Results (Training)
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```
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Sum Rewards: [0.0, 241.0, 57.0, 201.0, 48.0, 0.0, 0.0, 220.0, 262.0, 0.0,
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59.0, 211.0, 287.0, 187.0, 74.0, 2.0, 203.0, 18.0, 10.0, 0.0,
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0.0, 263.0, 7.0, 57.0, 39.0, 214.0, 297.0, 24.0, 0.0, 274.0,
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201.0, 2.0, 228.0, 228.0, 68.0, 290.0, 2.0, 222.0, 31.0, 219.0,
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69.0, 22.0, 0.0, 76.0, 244.0, 227.0, 0.0, 26.0, 192.0, 211.0]
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Successes: 21/50 episodes
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```
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## Limitations
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- **Limited training data**: Only 50 demonstration episodes available
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- **Moderate success rate**: This is a lightweight baseline model
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- **Single task**: Only trained on TransferCube, no multi-task capability
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## Citation
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```bibtex
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@article{zhao2023learning,
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title={Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware},
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author={Zhao, Tony Z and Kumar, Vikash and Levine, Sergey and Finn, Chelsea},
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journal={arXiv preprint arXiv:2304.13705},
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year={2023}
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}
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```
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## Acknowledgments
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- [LeRobot](https://github.com/huggingface/lerobot) framework by HuggingFace
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- [ALOHA](https://tonyzhaozh.github.io/aloha/) project by Stanford |
