A Kalman filter on the distance to a wall

Your wall_kf.py, running in this page: predict on every odometry step, update on every LiDAR scan.

LiDAR ON r 2 cm q 1 cm/√m K - σ -

Starting Python in the browser. The first time takes a few seconds.

Lecture run: LiDAR off from 12 to 17 s, as on the slides

Python not started yet.

The Python behind the demo

The page imports wall_kf.py as it is and steps its Sim and Filter. The keys from the plot window are the buttons.

Run the script's own headless check, exactly as on your Mac:

$ python3 wall_kf.py --sim --headless 25

Each tick of the live plot calls this, from the page's small driver: