Now what this thing does is it intercepts the input values from sensors so for example, from pressure sensors and vibration sensors and it provides legitimate program code, which is still running during the attack, with fake input data.

It then turns clockwise by pi 2 again, and moves 10 meters this time and I just want you to print out the sensor measurements after this entire procedure.

And the better the match, the higher the score.

We built a robot, and we make the robot move, and we now get a sensor measurement for that specific robot using the sense function.

It has lots of variables you can't really measure immediately, and it has sensors which allow you to understand a little bit about the state of the car.

You can see different rooms, and you can see corridors, and the robot is equipped with range sensors.

Of course, there are many different types of robots and they all interact with their environments through their sensors, which include things like cameras, microphones, tactile sensor or touch.

So the drag and the weight cancel.

So, there are 2 print statements for the sensor over here and the sensor measurements over here.

I do cover it in my book.

Sensor_right is the probability that the sensor measurement is correct.

This is the added Gaussian noise variable to the motion you command.

Some have 0.13, but the one over here has a probability of 0.533.

You should generate a URL that looks like this.

They can build a sensor without me.

You said it was done ad hoc in this little example, but in really designing a robot car, how do you decide on what these values are going to be?

Additionally, I give you two more variables called sensor_right and p_move.

We have the 2 room vacuum world, and we've represented various belief states here.

The cell on the right still wins, but now with a smaller total probability of just 0.46.

The motions don't move at all, move right, move down, move down, and move right again.

Good. You'll build the sensor for us...

Thrun Wow! You learned a lot about hidden Markov models and particle filters.

Switching to IR sensor.

So this robot is actually equipped with a camera, and a laser rangefinder, laser scanner.

This robot happens to know where north is at all times.

Initially this robot has no clue where it is. It faces what we call a global localization problem.

One of the fundamental things about robotics is called perception.

Let's execute this.

Rezero keeps his balance by constantly measuring his pitch angle with a sensor.

In fact, many of these vehicles are operated by flight crews that can include multiple pilots, operators of sensors, and mission coordinators.

They're pre engineered to be light, sound, motors and sensors.

That is called the control policy for the agent.

I'm not mad you built the sensor.

On board are also a battery, a computer, various sensors and wireless radios.

That's exactly what happened in our movie in the beginning when we looked at localization in this corridor environment.

The obvious answer is you killed that particle.

Listed as the logistician in the executive profile for SENSA, a privately funded think tank with offices in D.C,

It then turns clockwise by pi 2, which means you subtract pi 2 from the heading direction, and it moves 15 meters.

Now what's our mantra of this day and age I wonder?

These sensors continually shift the stimulation from one... nerve cluster to another, keeping the subject in a constant state of agony.

The very first approximation is physics.

Here is my intelligent agent, and it gets to interact with an environment.

We modified a Volkswagen Toureg to put all kinds of sensors onto the roof and actuators into the car that could actuate the steering wheel, the gas pedal, and the brake.

Values

With