Autonomous Vehicles: Boundary Tracking and

Control Laws

By Jackie Brosamer

June 19, 2008

Boundary Tracking

Goal given a density field, we want the vehicle to

find the boundary (where d(k) = B) and track along it

Basic algorithm rotate one way when inside the boundary

and the opposite way when outside boundary

Problem: Large initial crossing angle

Solution:

We modify our algorithm based on the time it takes to cross the boundary t and a predetermined reference angle

CUSUM filter

But this modification relies on accurate record of the boundary crossing times, so we need to find a way to deal eliminate noise in our data

We implement a cumulative sum algorithm to create a “high side” filter and a “low side” filter to increase accuracy

Multiple vehicle boundary estimation

We assume the approximate boundary is a Markov model based on the state of the system s(k)

Optimization

We then assume the boundary can be represented by an ellipse and formulate boundary estimation as an optimization problem

Steering Control Laws

Steer by altering the curvature of the vehicle’s path

Coupling Control Laws

Local coupling allows vehicles to follow other vehicles within their field of vision

Also, stronger coupling between a designated leader and followers

Homotopy parameter

Governs between global control law and local control law

Target Seeking

Separate control law, does not guarantee swarming

Barrier Avoidance

Average barrier direction given by:

We add the following term to steering control law :