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README.md

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-license: mit
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+---
+license: mit
+---
+<h1 align="center">
+	RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins<br>
+</h1>
+
+<a href="https://yaomarkmu.github.io/">Yao Mu</a><sup>* †</sup>, <a href="https://tianxingchen.github.io">Tianxing Chen</a><sup>* </sup>, Zanxin Chen<sup>* </sup>, Shijia Peng<sup>*</sup>,<br>Zeyu Gao, Zhiqian Lan, Yude Zou, Lunkai Lin, Zhiqiang Xie, <a href="http://luoping.me/">Ping Luo</a><sup>†</sup>.
+<br>
+
+**RoboTwin**: [Webpage (Coming Soon)]() | [PDF (Coming Soon)]() | [arXiv (Coming Soon)]()<br>
+**RoboTwin (early version)**, accepted to <i style="color: red; display: inline;"><b>ECCV Workshop 2024 (Oral)</b></i>: [Webpage](https://robotwin-benchmark.github.io/early-version) | [PDF](https://arxiv.org/pdf/2409.02920) | [arXiv](https://arxiv.org/abs/2409.02920)<br>
+<a href="https://hits.seeyoufarm.com"><img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FTianxingChen%2FRoboTwin&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Repo+Viewers&edge_flat=false"/></a>
+
+# ⏱️ Coming Soon
+1. Task Code Generation Pipeline.
+2. RoboTwin (Final Version) will be released soon.
+3. Real Robot Data collected by teleoperation.
+4. More Tasks env.
+5. More baseline code will be integrated into this repository (RICE, ACT, Diffusion Policy).
+
+# 📚 Overview
+![Expert Data Generation](./files/pipeline.png)
+![](./files/robotwin_task.png)
+
+# 🛠️ Installation
+See [INSTALLATION.md](./INSTALLATION.md) for installation instructions. It takes about 20 minutes for installation.
+
+# ℹ️ Task Informaction
+Coming Soon
+
+# 🧑🏻‍💻 Usage 
+## 1. Task Running and Data Collection
+Run `run_task.sh` to run task:
+```
+bash run_task.sh ${task_name} ${gpu_id}
+```
+The default task running configurations can be found at `config/${task_name}.yml`, if you want to change some task setting, just modify the specific configuration file.
+
+RoboTwin will run expert check first to make sure only successful data will be collect (by running seeds one by one first), this will not take too long.
+
+The Data will be collect to `data` under the root directory, in the form of `.pkl` usually.
+
+## 2. Task Config
+Data collection configurations are located in the `config` folder, corresponding to each task. Here is an explanation of the important parameters:
+
+1. **render_freq**: Set to 0 means no rendering. If you wish to see the rendering, it can be set to 10.
+2. **collect_data**: Data collection will only be enabled if set to True.
+3. **camera_w,h**: These are the camera parameters, with a total of 4 cameras - two on the wrist and two positioned as top and front views.
+4. **pcd_crop**: Determines whether the obtained point cloud data is cropped to remove elements like tables and walls.
+5. **pcd_down_sample_num**: The point cloud data is downsampled using the FPS (Farthest Point Sampling) method, set it to 0 to keep the raw point cloud data.
+6. **data_type/endpose**: The 6D pose of the end effector, which still has some minor issues.
+7. **data_type/qpos**: Represents the joint action.
+8. **observer**: Decides whether to save a observer-view photo for easy observation.
+
+## 3. Deploy your policy
+See `envs/base_task.py`, search `TODO` and you may see the following code, make sure that `policy.get_action(obs)` will return action sequence (predicted actions).:
+```
+actions = model.get_action(obs) # TODO, get actions according to your policy and current obs
+```
+
+You need to modify `script/eval_policy.py` in the root directory to load your model for evaluation: Search `TODO`, modify the code to init your policy. 
+
+Run the follow command to run your policy in specific task env:
+```
+bash script/run_eval_policy.sh ${task_name} ${gpu_id}
+```
+
+## 4. DP3 as baseline
+The DP3 code can be found in `policy/3D-Diffusion-Policy`.
+
+Process Data for DP3 training after collecting data (In root directory), and input the task name and the amount of data you want your policy to train with:
+```
+python script/pkl2zarr_dp3.py
+```
+
+Then, move to `policy/3D-Diffusion-Policy` first, and run the following code to train DP3 :
+```
+bash train.sh ${task_name} ${expert_data_num} ${gpu_id}
+```
+
+Run the following code to eval DP3 for specific task:
+```
+bash eval.sh ${task_name} ${expert_data_num} ${gpu_id}
+```
+
+Current leaderboard:
+```
+Here's the revised table with the averages listed at the end:
+
+|     Task                       |     Algorithm       |   10 demos   |   20 demos   |   50 demos   |
+|--------------------------------|---------------------|--------------|--------------|--------------|
+| Apple Cabinet Storage          | DP3 (XYZ)           | 41%          | 59%          | 75%          |
+|                                | DP3 (XYZ+RGB)       | 22%          | 41%          | 60%          |
+| Block Handover                 | DP3 (XYZ)           | 55%          | 89%          | 70%          |
+|                                | DP3 (XYZ+RGB)       | 48%          | 81%          | 94%          |
+| Block Stack (Easy)             | DP3 (XYZ)           | /            | /            | /            |
+|                                | DP3 (XYZ+RGB)       | 0%           | 1%           | 23%          |
+| Container Place                | DP3 (XYZ)           | 34%          | 54%          | 68%          |
+|                                | DP3 (XYZ+RGB)       | 18%          | 28%          | 54%          |
+| Dual Bottles Pick (Easy)       | DP3 (XYZ)           | 10%          | 48%          | 78%          |
+|                                | DP3 (XYZ+RGB)       | 9%           | 41%          | 75%          |
+| Empty Cup Place                | DP3 (XYZ)           | 3%           | 30%          | 73%          |
+|                                | DP3 (XYZ+RGB)       | 7%           | 23%          | 82%          |
+| Pick Apple Messy               | DP3 (XYZ)           | 2%           | 2%           | 9%           |
+|                                | DP3 (XYZ+RGB)       | 2%           | 3%           | 25%          |
+| Shoes Place                    | DP3 (XYZ)           | 2%           | 1%           | 12%          |
+|                                | DP3 (XYZ+RGB)       | 0%           | 0%           | 5%           |
+| Block Hammer Beat              | DP3 (XYZ)           | 37%          | 45%          | 60%          |
+|                                | DP3 (XYZ+RGB)       | 36%          | 41%          | 73%          |
+| Block Sweep                    | DP3 (XYZ)           | 49%          | 80%          | 96%          |
+|                                | DP3 (XYZ+RGB)       | 70%          | 98%          | 99%          |
+| Block Stack (Hard)             | DP3 (XYZ)           | /            | /            | /            |
+|                                | DP3 (XYZ+RGB)       | 0%           | 0%           | 3%           |
+| Diverse Bottles Pick           | DP3 (XYZ)           | 3%           | 12%          | 38%          |
+|                                | DP3 (XYZ+RGB)       | 0%           | 1%           | 7%           |
+| Dual Bottles Pick (Hard)       | DP3 (XYZ)           | 13%          | 29%          | 46%          |
+|                                | DP3 (XYZ+RGB)       | 11%          | 26%          | 48%          |
+| Mug Hanging                    | DP3 (XYZ)           | 1%           | 9%           | 13%          |
+|                                | DP3 (XYZ+RGB)       | 1%           | 2%           | 6%           |
+| Shoe Place                     | DP3 (XYZ)           | 12%          | 16%          | 54%          |
+|                                | DP3 (XYZ+RGB)       | 13%          | 20%          | 35%          |
+| Average                        | DP3 (XYZ)           | 20.15%       | 36.46%       | 53.23%       |
+|                                | DP3 (XYZ+RGB)       | 17.93%       | 29.33%       | 45.93%       |
+
+```
+
+# 🪄 Digital Twin Generation
+
+Deemos Rodin: [https://hyperhuman.deemos.com/rodin](https://hyperhuman.deemos.com/rodin)
+
+# ⁉️ Common Issues
+If you find you fail to quit the running python process with `Crtl + C`, just try `Ctrl + \`.
+
+We found Vulkan is not stable in someoff-screen devices, try reconnecting `ssh -X ...` if you meet any problem.
+
+Other Common Issues can be found in [COMMON_ISSUE](./COMMON_ISSUE.md)
+
+# 👍 Citation
+If you find our work useful, please consider citing:
+
+1. RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins
+```
+Coming Soon
+```
+
+2. RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (**early version**), accepted to <i style="color: red; display: inline;"><b>ECCV Workshop 2024 (Oral)</b></i>
+```
+@article{mu2024robotwin,
+  title={RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version)},
+  author={Mu, Yao and Chen, Tianxing and Peng, Shijia and Chen, Zanxin and Gao, Zeyu and Zou, Yude and Lin, Lunkai and Xie, Zhiqiang and Luo, Ping},
+  journal={arXiv preprint arXiv:2409.02920},
+  year={2024}
+}
+```
+
+# 🏷️ License
+This repository is released under the MIT license. See [LICENSE](./LICENSE) for additional details.