gym-aloha-dummy 0.1.0
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Requires Python: >=3.11

# gym-aloha

A gym environment for ALOHA with custom dummy robot model

<img src="https://s2.loli.net/2025/02/20/wHSPmZL4NVMnYOz.gif" width="50%" alt="Example of ALOHA Dummy env"/>

## Installation

Install [UV](https://docs.astral.sh/uv/getting-started/installation/) then:

```bash
git clone https://github.com/aod321/gym-aloha.git
cd gym-aloha
git checkout -b dummy_robot
uv sync
uv add --dev .
```


## Quickstart

```bash
uv run example.py
```


## Description
Aloha environment.

Two tasks are available:
- TransferCubeTask: The right arm needs to first pick up the red cube lying on the table, then place it inside the gripper of the other arm.
- InsertionTask: The left and right arms need to pick up the socket and peg respectively, and then insert in mid-air so the peg touches the “pins” inside the socket.

### Action Space
The action space consists of continuous values for each arm and gripper, resulting in a 14-dimensional vector:
- Six values for each arm's joint positions (absolute values).
- One value for each gripper's position, normalized between 0 (closed) and 1 (open).

### Observation Space
Observations are provided as a dictionary with the following keys:

- `qpos` and `qvel`: Position and velocity data for the arms and grippers.
- `images`: Camera feeds from different angles.
- `env_state`: Additional environment state information, such as positions of the peg and sockets.

### Rewards
- TransferCubeTask:
    - 1 point for holding the box with the right gripper.
    - 2 points if the box is lifted with the right gripper.
    - 3 points for transferring the box to the left gripper.
    - 4 points for a successful transfer without touching the table.
- InsertionTask:
    - 1 point for touching both the peg and a socket with the grippers.
    - 2 points for grasping both without dropping them.
    - 3 points if the peg is aligned with and touching the socket.
    - 4 points for successful insertion of the peg into the socket.

### Success Criteria
Achieving the maximum reward of 4 points.

### Starting State
The arms and the items (block, peg, socket) start at a random position and angle.

### Arguments

```python
>>> import gymnasium as gym
>>> import gym_aloha
>>> env = gym.make("gym_aloha/AlohaInsertion-v0", obs_type="pixels", render_mode="rgb_array")
>>> env
<TimeLimit<OrderEnforcing<PassiveEnvChecker<AlohaEnv<gym_aloha/AlohaInsertion-v0>>>>>
```

* `obs_type`: (str) The observation type. Can be either `pixels` or `pixels_agent_pos`. Default is `pixels`.

* `render_mode`: (str) The rendering mode. Only `rgb_array` is supported for now.

* `observation_width`: (int) The width of the observed image. Default is `640`.

* `observation_height`: (int) The height of the observed image. Default is `480`.

* `visualization_width`: (int) The width of the visualized image. Default is `640`.

* `visualization_height`: (int) The height of the visualized image. Default is `480`.


## Contribute

Instead of using `pip` directly, we use `poetry` for development purposes to easily track our dependencies.
If you don't have it already, follow the [instructions](https://python-poetry.org/docs/#installation) to install it.

Install the project with dev dependencies:
```bash
poetry install --all-extras
```


### Follow our style

```bash
# install pre-commit hooks
pre-commit install

# apply style and linter checks on staged files
pre-commit
```


## Acknowledgment

gym-aloha is adapted from [ALOHA](https://tonyzhaozh.github.io/aloha/)