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Remi Cadene
2025-04-17 04:46:09 +02:00
parent 6b6a990f4c
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examples/11_use_moss.md
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@@ -31,16 +31,15 @@ conda create -y -n lerobot python=3.10 && conda activate lerobot
git clone https://github.com/huggingface/lerobot.git ~/lerobot
```
5. Install LeRobot with dependencies for the feetech motors:
5. Install ffmpeg in your environment:
When using `miniconda`, install `ffmpeg` in your environment:
```bash
cd ~/lerobot && pip install -e ".[feetech]"
conda install ffmpeg -c conda-forge
```
For Linux only (not Mac), install extra dependencies for recording datasets:
6. Install LeRobot with dependencies for the feetech motors:
```bash
conda install -y -c conda-forge ffmpeg
pip uninstall -y opencv-python
conda install -y -c conda-forge "opencv>=4.10.0"
cd ~/lerobot && pip install -e ".[feetech]"
```
## Configure the motors
@@ -176,8 +175,8 @@ Next, you'll need to calibrate your Moss v1 robot to ensure that the leader and
You will need to move the follower arm to these positions sequentially:
| 1. Zero position | 2. Rotated position | 3. Rest position |
|---|---|---|
| 1. Zero position | 2. Rotated position | 3. Rest position |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| <img src="../media/moss/follower_zero.webp?raw=true" alt="Moss v1 follower arm zero position" title="Moss v1 follower arm zero position" style="width:100%;"> | <img src="../media/moss/follower_rotated.webp?raw=true" alt="Moss v1 follower arm rotated position" title="Moss v1 follower arm rotated position" style="width:100%;"> | <img src="../media/moss/follower_rest.webp?raw=true" alt="Moss v1 follower arm rest position" title="Moss v1 follower arm rest position" style="width:100%;"> |
Make sure both arms are connected and run this script to launch manual calibration:
@@ -192,8 +191,8 @@ python lerobot/scripts/control_robot.py \
**Manual calibration of leader arm**
Follow step 6 of the [assembly video](https://www.youtube.com/watch?v=DA91NJOtMic) which illustrates the manual calibration. You will need to move the leader arm to these positions sequentially:
| 1. Zero position | 2. Rotated position | 3. Rest position |
|---|---|---|
| 1. Zero position | 2. Rotated position | 3. Rest position |
| ------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| <img src="../media/moss/leader_zero.webp?raw=true" alt="Moss v1 leader arm zero position" title="Moss v1 leader arm zero position" style="width:100%;"> | <img src="../media/moss/leader_rotated.webp?raw=true" alt="Moss v1 leader arm rotated position" title="Moss v1 leader arm rotated position" style="width:100%;"> | <img src="../media/moss/leader_rest.webp?raw=true" alt="Moss v1 leader arm rest position" title="Moss v1 leader arm rest position" style="width:100%;"> |
Run this script to launch manual calibration:
@@ -219,6 +218,9 @@ python lerobot/scripts/control_robot.py \
**Teleop with displaying cameras**
Follow [this guide to setup your cameras](https://github.com/huggingface/lerobot/blob/main/examples/7_get_started_with_real_robot.md#c-add-your-cameras-with-opencvcamera). Then you will be able to display the cameras on your computer while you are teleoperating by running the following code. This is useful to prepare your setup before recording your first dataset.
> **NOTE:** To visualize the data, enable `--control.display_data=true`. This streams the data using `rerun`.
```bash
python lerobot/scripts/control_robot.py \
--robot.type=moss \
@@ -293,14 +295,14 @@ python lerobot/scripts/train.py \
--policy.type=act \
--output_dir=outputs/train/act_moss_test \
--job_name=act_moss_test \
--device=cuda \
--policy.device=cuda \
--wandb.enable=true
```
Let's explain it:
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/moss_test`.
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
Training should take several hours. You will find checkpoints in `outputs/train/act_moss_test/checkpoints`.