EarthRover Mini Plus

The EarthRover Mini Plus is a fully open source mobile robot that connects through the cloud using the Frodobots SDK. This lets you control the robot and record datasets for training AI models.

What You Need

Hardware

• EarthRover Mini robot
• Computer with Python 3.10 or newer
• Internet connection

Setting Up the Frodobots SDK

The robot needs the Frodobots SDK running on your computer. Here’s how:

1. Download and install the SDK:

git clone https://github.com/Frodobots/earth-rovers-sdk.git
cd earth-rovers-sdk
pip install -r requirements.txt

2. Start the SDK:

hypercorn main:app --reload

3. Open your web browser and go to http://localhost:8000, then click “Join”

The SDK gives you:

• Live video from front and rear cameras

The SDK must be running before you can use the robot.

Install LeRobot

Follow our Installation Guide to install LeRobot.

In addition to the base installation, install the EarthRover Mini dependencies:

pip install -e .

How It Works

The robot uses the internet to communicate:

• Movement commands: Sent through the SDK
• Camera video: Received from the SDK
• Robot info: Battery, location, speed from the SDK

You don’t need to plug anything in - it all works through the SDK.

Calibration

No calibration needed! The robot is ready to use as soon as the SDK is running.

Controlling the Robot

You control the robot using your keyboard - just like playing a video game with WASD keys.

Keyboard Controls

Speed Settings

You can adjust how fast the robot moves:

• Forward/backward speed: Default is full speed (1.0)
• Turning speed: Default is full speed (1.0)
• Speed changes: Use +/- keys to adjust by 0.1 each time

Try It Out

Test driving the robot before recording data:

from lerobot.robots.earthrover_mini_plus import EarthRoverMiniPlus, EarthRoverMiniPlusConfig
from lerobot.teleoperators.keyboard import KeyboardRoverTeleop, KeyboardRoverTeleopConfig

# Initialize robot
robot_config = EarthRoverMiniPlusConfig()
robot = EarthRoverMiniPlus(robot_config)

# Initialize teleoperator
teleop_config = KeyboardRoverTeleopConfig(
    linear_speed=1.0,
    angular_speed=1.0,
    speed_increment=0.1
)
teleop = KeyboardRoverTeleop(teleop_config)

# Connect
robot.connect()
teleop.connect()

# Teleoperate (use keyboard controls)
try:
    while True:
        action = teleop.get_action()
        robot.send_action(action)
except KeyboardInterrupt:
    pass
finally:
    robot.disconnect()
    teleop.disconnect()

If you’re using a Mac, you might need to give Terminal permission to access your keyboard for teleoperation. Go to System Preferences > Security & Privacy > Input Monitoring and check the box for Terminal.

Recording Data

Once you can drive the robot well, you can start recording data to train AI models. The system records:

• What you do: How you move the robot (forward, backward, turning)
• What the robot sees:
  • Videos from both cameras
  • Robot speed and direction
  • Battery level and location
  • GPS position and signal
  • Other sensor data
• When it happened: Timestamps for everything

Setting Up Hugging Face

We use Hugging Face to store your data online. First, log in with your token from Hugging Face settings:

huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential

Store your Hugging Face username:

HF_USER=$(huggingface-cli whoami | head -n 1)
echo $HF_USER

Start Recording

Use the standard recording command:

python src/lerobot/scripts/lerobot_record.py \
    --robot.type=earthrover_mini_plus \
    --teleop.type=keyboard_rover \
    --dataset.repo_id=your_username/dataset_name \
    --dataset.num_episodes=2 \
    --dataset.fps=10 \
    --dataset.single_task="Navigate around obstacles" \
    --display_data=true

Replace your_username/dataset_name with your Hugging Face username and a name for your dataset.

What Gets Saved

Your dataset includes:

Your Actions (2 things):

• How much you moved forward/backward
• How much you turned left/right

Robot Observations (12 things):

• Front camera video
• Rear camera video
• Current speed
• Battery level
• Which way the robot is facing
• GPS location (latitude, longitude, signal strength)
• Network signal strength
• Vibration level
• Lamp status (on/off)

Where Your Data Goes

On your computer: ~/.cache/huggingface/lerobot/{repo-id}

After recording, your data automatically uploads to your Hugging Face page:

echo https://huggingface.co/datasets/${HF_USER}/earthrover-navigation

Your dataset will be tagged with LeRobot for community discovery.