---
tags:
- robotics
- imitation-learning
- act
- isaac-lab
- galaxea
library_name: generic
---

# ACT Policy for Gearbox Assembly

This model is an **Action Chunking with Transformers (ACT)** policy trained for a gearbox assembly task in Isaac Lab.

## Model Details
- **Architecture**: ACT (Action Chunking with Transformers)
- **Task**: Gearbox Assembly
- **Framework**: Isaac Lab / PyTorch
- **Dataset**: `sim_gearbox_assembly_demos_filtered`

## Training Data Usage
The model was trained using **all available episodes** from the provided dataset.

### Important Data Characteristics
- **Process Simplification**: The **pin insertion step was omitted** in all training episodes. The task focuses on the steps following pin insertion (e.g., gear mounting, cover installation).
- **Data Quality Note**: The training set deliberately includes one known **failed episode** where a pin fell over during the process, causing the subsequent cover installation to fail. This episode was **not filtered out** and was used in training.

## Hyperparameters
The model was trained with the following configuration:

| Parameter | Value |
|:---|:---|
| **Policy Class** | ACT |
| **KL Weight** | 10 |
| **Chunk Size** | 100 |
| **Hidden Dim** | 512 |
| **Feedforward Dim** | 3200 |
| **Batch Size** | 32 |
| **Learning Rate** | 1e-5 |
| **Epochs** | 10000 |
| **Seed** | 0 |
| **Save Interval** | 200 |
| **Early Stopping** | 3000 |

## Usage
This model is designed to be loaded with the ACT policy wrapper in the Galaxea Lab framework for the `GalaxeaLab-GearboxAssembly` environment.