Contact.

The vehicle is actually modeled as a system with 2 non steerable wheels and 2 steerable wheels.

Here is the problem.

My turning angle, I called turn.

Forward left, one quarter. Stern right full.

Steering has several nonlinear effects... saturation, deadzone, ratelimiting...

The helm's not responding.

The rudder cables became useless and I lost my ability to steer.

Let's assume the car has a fixed forward velocity, but you have the ability to set the steering angle of the car.

I should warn you that sometimes I do get collisions here, and it's because our obstacle surfaces are relatively large.

Please move away from the controls, captain.

R times the sine of theta, and cy is equal to the initial y position plus this extra distance, R times the cosine of theta.

It then reduces y over time to go into negative territory.

Looking at him, I could see white sails and blue water.

The Helmsman and the Armoury Officer are back on the Bridge.

I'm leaving you in command. Get the ship operational.

If I set the mean of the Gaussian to be the steering command and the distance command then this adds noise.

You can see the steering tends to be on the negative side.

The crosstrack_error by and large is very small.

Steering

During the day, the Nutmeg collects energy from solar panels on the roof of the wheelhouse, and from a 450 watt turbine up the mast.

We manipulate this equation a little bit, and we find that the radius of curvature is equal to the length of the vehicle over the tangent of the steering angle.

Here I'll apply the noise, which you don't need it for the first implementation, but later on as we go on, you need it to actually add noise.

Suppose you do what I just said. You steer in proportion to the crosstrack error.

This is needed for cross domain communication purposes.

So you start steering more and more the more time goes by to the right to compensate this bias.

That's measured by the integral or the sum of the crosstrack errors over time.

But let's try this out with out our proportional controller.

Put differently, the robot oscillates a bit like this with a fairly constant new offset error due to this bias.

That is, it's not just points in x y space, but it's successive state vectors for cars.

I make a new robot copy as in my sample code in class.

A constant steering will put you in a circle and not in a straight line.

We moved everything to the wheels, so you have the drive motor, the steering motor, the breaking all in the wheel.

Then we apply the corresponding new motion model to x and y to obtain x2 and y2.

I just add Gaussian noise with the corresponding steering noise and distance noise parameters.

What's the intuition?

You will reach the trajectory. Clearly the other two answers are really bad.

As a result, when you drive you steer the car this way.

I like to see a gymnast do the giant swing on the high bar.

Not much. Just that he's an Olympic gymnast and it's the best sex she's ever had.

So what we are doing is an accelerated evolution of sailing technology.

The second part we didn't talk much about is selection of speed.

We chose the Helmsman and the Armoury Officer for good reason.

Can you steer a course?

It'll make a great tail.