System identification — drone

Draft

This tutorial is scaffolded. It narrates examples/vehicles/sysid_drone.py, which is complete and runnable today.

Fit a drone's physical parameters (mass, thruster gains, mount transforms) to a recorded log using Fit.

To cover

• Declaring promotable Parameters (those with a manifold=) and what promotion does (Sim(world, parameters=[...]) → a params port).
• Building Windows from logged controls + measurements.
• Running the MAP fit, reading FitResult, checking converged.
• Pitfalls: whiten sensors; σ is not L2-fittable (use NoiseFit for that); joint-space A can be legitimately singular.

Run it

python -m examples.vehicles.sysid_drone

Source material

• Code: examples/vehicles/sysid_drone.py
• Reference: System identification
• How-to: Fit parameters from a log