Helicopter Controller: iLQR and Inverse Optimal Control

In this work, DDP was first used to find a controller that flies the helicopter following certain trajectory.  Inverse optimal control is then implemented based on the demonstrated trajectories from the given controller. The learned Q and R are computed  by doing subgradients on the cost functions of linearly weighted features and the loss between demoed trajectories and true trajectories, and finally the projection to the convex cone of positive semi-definite matrices.

The learned Q is denser than the given; the controller is similar to the given:

QKss2

And the cost is decresed as follows:

cost

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: