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