Kalman Filter: Depth-Estimator Example

We use a Jupyter notebook. So instead of having a ‘live’ simulation in ROS, we run a simulation with a predefined time span, all at once. We also have to include some code that simulates the real system. In ROS, these data would come from either Gazebo or the real world.

Download the Code

Do not clone this repository into the ROS2 workdpace.

$ cd && git clone https://github.com/FormulasAndVehicles/depth_estimator_notebook.git

$ cd depth_estimator_notebook

Create a virtual environment

$ python3 -m venv venv

Source the environment

$ source venv/bin/activate

Install the dependencies

$ python3 -m pip install -r requirements.txt

Open the Notebook

$ jupyter notebook

A new browser tab should open. Open the notebook by right clicking ekf_example.ipynb

and selecting Open with ‣ Notebook