All language subtitles for How.Tech.Works.S01E10.WEBRip.x264-ION10

[narrator] On this episode
of How Tech Works...

we get exclusive access

to the latest
military transport vehicle.

It's as versatile
as a passenger van,

but it's built for the skies,
not the suburbs.

And, we'll meet a robot
that can predict exactly

where a moving object will land.

Sounds like
a cricketer's dream.

[show intro]

[futuristic music]

Hello there!
I'm Dr. Basil Singer

and you won't want to be
anywhere but right here

for the next half hour,
as we explore

the latest advances
in science and technology,

and awesome robots that
do cool things.

I'm talking a real,
life-sized robot car

that can drive itself,
down the Autobahn!

And, I'm talking
a vertical wind tunnel

that lets you skydive indoors!

But first...

We here at How Tech Works
like things that are big.

Really, really big.

So we thought we'd take off
with a massive plane

from Seville, in Spain.

It's called the Airbus A400M,

and it's one of the world's
biggest air transport planes.

Here's our exclusive
behind-the-scenes tour

of what makes it tick.

[rock music]

[narrator] You're looking
at a test model

of one of the most
massive planes ever.

This is the A400M,
designed to challenge

the air transport planes
that currently rule the sky.

At 45 meters long,
it's a whale of a plane.

Bigger than an AC-130 Hercules.

But like the Hercules,

it's designed for both
military missions,

and humanitarian aid.

It can even serve as
a petrol station in the sky,

refueling other aircraft
in-flight

or taking fuel onboard.

One look at the cargo hold
says it all.

The cargo hold has a maximum
capacity of 37 tonnes.

That means we can transport
a wide variety of things,

like skydivers,
paratroopers, medivac,

even helicopters,
without rotor blades, of course.

It can drop cargo
at a low speed and altitude,

and land on short runways
without any prior preparation.

[narrator] It's one of
the most powerful transports

on the planet,
with four turboprop engines

providing a total of
11,000 horsepower.

Okay, so it's a monster.
But what's it like to fly?

It's a big truck, but it
flies a bit like a sports car.

[narrator] Test pilot
Tony Flynn has taken it out

for a few test drives.

We can go to 120 degrees
angle of bank,

we can go to 3G,

but of course,
with that comes responsibility,

because it doesn't matter
how good the sports car is,

you can still drive her
off the road.

[narrator] That's why
the mechanical controls

are different than in a car,
or even an older plane.

[Tony] In most old airplanes,

the joystick at the front
is connected mechanically

to the flight control systems
on the airplane.

What we've done is we've
removed that mechanical link

so the pilot is connected
to a computer.

[narrator] The computer system
is called fly-by-wire.

It's programmed to guess
what the pilot wants,

but to fly within safe limits.

[Tony] There is a G limit,

so he cannot
overstretch the airplane,

he cannot stall the airplane
and make it go too slow.

[narrator] The A400M
is driven by propellers.

That gives it an advantage
over traditional jet engines.

The large transport C17,

when it lands on an unprepared
strip in the desert,

lots of stones will be
sucked up into the engines

and causing engine damage.

and what propellers allow us
to do is to land

on unprepared strips without
sustaining the type of damage

that a jet engine would suffer.

[narrator] Tony's going
to take the A400M

-out for another test drive.
-Off we go!

[narrator] But before he does,
he's taking us inside,

for an exclusive look
at the cockpit,

one of the most advanced in
a transport aircraft anywhere.

We've got eight TV screens
in the cockpit.

We can configure these screens
for each mission

For example,
on the displays behind me,

on one display right now
we can have the map,

I can put up a terrain display,
so I cannot fly into a hill.

Just by pressing
one button here

the weather radar is now
displayed, which will show

any bad weather ahead of me,

which I can avoid
and not fly into.

[narrator] If all that fails,
the pilot can still fly

with the head's up display,
which shows him

all the essentials.
Air speed, altitude,

flight path,
and an infrared mode

so he can see at night,
even in bad weather.

What it allows the pilot to do
is to fly tactically,

for example at low altitude,
whilst looking

out of the window.
But at the same time,

he's able to read
the information

directly in front of his eyes.

[narrator] All the technology
provides some comfort.

But there are more comforts
built in. It's kind of like

driving an incredibly big,
high tech camper van.

It's very comfortable,
the seats are well-designed,

the whole space
is very well-designed,

and it's a nice place
to go to work.

In fact, we even have some
very nice and very expensive

meal tray holders where we can
have dinner during the flight.

[narrator] No time for lunch.
He's gotta fly.

Tony and his colleagues
are checking everything

from the plane's
maneuverability

to wing performance.
The wings are ultralight,

made entirely of carbon fiber.

One of the technologies
that stands out

is the use of carbon fiber.

The wings are designed and built
with carbon fiber,

as well as the vertical
and horizontal stabilizers,

air frame and engine.

This reduces weight
and fuel needs.

[narrator] The team is also
pushing the limits

of the onboard technologies.

Every flight test, and all
data collected in-flight,

is monitored by engineers
on the ground

in Spain, France,
Germany and England.

[English voice-over] Engineers
both in the plane

and on the ground can detect

any flaws in any
of the systems

and communicate with the
pilots in real-time.

[narrator] Mission
accomplished.

[Tony] When the flight test goes
right, you definitely feel

a sense of achievement,
and you come away feeling

you've done a good day of work.

So clearly that mega-plane
is a perfect example

of a man-made machine doing
work that we, mere mortals,

can't do alone!

Let's face it, we rely
more and more on machines

and computers these days.

But sometimes the simplest
human task is not all that

easy for high tech machines.

Now, if you need any proof
of that, enter exhibit A.

From the tech team
at UC Berkeley,

I present to you,
the Quadrotor.

[upbeat music]

[narrator] Most of us take
catching a ball for granted.

We see it, track it, we run
and then we catch it.

It sounds really easy, right?

But for the computerized
Quadrotor helicopter,

It's actually got complicated
calculations to make

in order to catch the ball.

Ready... set... go!

The motion capture system
finds these reflective dots,

and using this, determines
the position

of the Quadrotor helicopter,
and to track the ball

we cover it
with reflective tape.

[narrator] Humans don't track
an airborne ball the same way.

A human baseball player
is trying to maintain

a constant angle in their
field of view to the ball.

So they're basically tracking
it in their visual system,

and trying to keep it
roughly in the same spot.

And if that holds
the entire time,

eventually the ball
has to come towards them.

[narrator] The Quadrotor
has got the help

of near-infrared motion
capture cameras.

That information helps it
predict where the ball

will land, so it can move
there to catch it.

At each instant in time,
the helicopter is getting

a measurement of the instant
position of the ball.

It then uses an idea
of the physics of the ball

to predict
where it will land.

[narrator] Pat Bouffard got
the Quadrotor up and running.

It's quite capable of
moving around on its own,

based on commands.

Anil Aswani is now on board,
adapting a new technique

he calls "learning-based model
predictive control." Wow.

It basically gives machines
that were previously automated

the ability to learn, adapt,
and make decisions.

The technique is called
"predictive control" because

the machine uses its internal
model of its behavior

to predict
how it's going to behave.

[narrator] In this case,
the Quadrotor makes

its predictions based on
information it receives

from the cameras set up
around the room.

The camera system is kind of
a general positioning device

that allows us to figure out
where the Quadrotor is

and where the ball is.

[narrator] Instantaneous
measurements are happening

one hundred and twenty
times a second!

We use the camera system
to determine the position

of the ball, and then we look
at the position over time

to try to determine what
the trajectory of the ball

is gonna be. In other words,

how the ball is gonna go up
and curve and come down.

[narrator] The red cross marks
the predicted landing spot

of the ball. The Quadrotor
constantly adjusts that spot,

throughout the ball's arc.

Because all this happens
very quickly, we have to have

a pretty good prediction
right off the bat.

[narrator] They need
to accurately predict

the ball's trajectory through
the air, once it's thrown.

There was a lot
of trial and error.

And that was really trying
to determine which forces

are the most significant
forces on the ball.

Gravity, in this case, is by
far the most important factor,

because it's always there,
and it's very much constant

and quite predictable.

There's also air resistance,

which tends to slow
the ball down,

and that's a fairly
well-understood effect.

[narrator] The instant
the ball is thrown,

the Quadrotor's prediction
is accurate

to within ten centimeters.

But within one second
of calculations,

and by the time
the ball's about to land,

it's accurate
to under one centimeter.

It catches the ball
about 90% of the time.

Better than my
fielding percentage.

But they still think
they can do better.

There's a phenomenon that
causes the path of the ball

to curve,
because of the spin.

But it ended up below our
threshold of modeling,

so we decided
not to include that.

But if we were
to include this in future,

that might improve
our performance and accuracy.

[narrator] So while humans
continue to keep

their eye on the ball using
their own built-in visual clues,

Anil and Pat will continue
to work with the Quadrotor,

which takes its cues from
tracking systems

in the outside world.

[Anil] Humans often use
approximate techniques that work

very well in practice,
whereas machines have to use

very complex mathematical
algorithms in order

to replicate what humans do.

And that's a very interesting
area of research

on trying to bridge the gap,
and that's one

that we may look into
in the future

Coming up on How Tech Works.

Here's a car
you have to see to believe.

and that's
all you have to do,

because this car drives
itself... down the Autobahn!

And, we'll check out the world's
biggest vertical wind tunnel,

and go sky-diving... indoors!

Welcome back to How Tech Works.
I'm Basil Singer,

your host with the most
ridiculous love

for all things robot
and remote controlled.

So, without further ado,

we catch up with intrepid
reporter Dan Riskin,

driving on the super fast
Autobahn in Germany,

where, ordinarily,
it's critical to stay focused

on the task at hand.

Except when you don't
need your hands!

[narrator] The Autobahn.
When you drive it,

you've gotta keep
your eyes on the road

and your hands upon the wheel.

Unless you're in this car.
Look, Ma, no hands!

It's a robot car called
Made in Germany,

"MIG" for short.

Made by researchers at
the Free University of Berlin.

[speaking German]

[narrator] And today,
for the very first time,

They'll let it overtake
another car

in heavy Autobahn traffic,
all by itself.

But first, a warm up.
MIG's going to drive itself

through Berlin traffic.

And I'm going to catch a ride.

[narrator] Two researchers
are on board to ensure safety.

But I'm still
nervous about this.

Alright, here we are.
What are you looking at?

I am looking at the sensor
readings of the car.

I have the plan where the car
wants to go.

[Dan] So the map of the roads

is from a map that
it has in its brain?

[man] Yeah,
it's stored in a file.

Right now, I'm in control

and as soon as I put
my foot off the brake pedal.

[Dan] Holy shoot!
Okay, I can't swear.

[man] So now the car wants
to go left on the trajectory.

Three, two, one, go.

So this is driving
by itself now?

Yes. It is driving
totally by itself.

I don't do anything.
My hands are off.

It's going a little fast,
it really accelerated quickly.

[man] Yeah it's 50. We didn't
want to drive like Grandma,

so it's just normal driving.

[Dan laughs] You didn't want to
drive like Grandma?

Is that what you just said?
[laughs]

[narrator] The goal is to make
an autopilot that can

stop accidents from happening,

and eventually make cars that
drive themselves all the time.

Could you go to sleep?

I cannot go to sleep
because all the time

there can something happen,
and there can be

unexpected situations the car
cannot handle,

and then I have to intervene.
I only have to put my foot

on the brake or on the gas
and then I am in control again.

[Dan] So how long have you had
permission to drive this

on the roads of Berlin?

[man] So we just got
the permission this week.

This week! So this still
pretty brand new for you guys.

Yeah, it is.

[narrator] The team has
permission to let MIG

drive itself, back and forth,
on this busy boulevard.

[Dan] There's a lot
of traffic here!

[man] Yeah,
because it's a big road.

[narrator] I try hard to look
calm at the first U-turn.

Okay, so now you have
a cyclist who is trying

to cross, so this is a spot
where she might just pull out.

Yeah, she's going. So the car
sees her, and hits the break.

The car recognized her.
And she stopped.

She is gone.
So we can continue.

[Dan] So that was all the car?

-[man] Yes, it was all the car.
-[Dan] That's great!

[narrator] MIG sees the world
with a laser sensor up top.

And laser and radar sensors
built in the body, and cameras.

The images are processed by a
computer in the trunk.

GPS tells it where it is.

Everything feeds into
another computer,

which controls motors working
the accelerator, brakes,

and steering. Miao's laptop
controls it all.

The red shapes are cars
and other obstacles.

So we're coming up to a turn
there, is that what that shows?

Yeah, it is making
a U-turn here.

[narrator] But this is still
a work in progress.

The car stops,
and starts, and stops.

And when the road is clear,
he will pursue his path.

So right now it doesn't
start on its own

because there is grass
on the street on our right side.

Just this little grass
on the side here?

Yeah, so therefore I took over.

And now I give control
back to the car.

And now it starts accelerating.

[Dan] That's what
that beeping noise was?

[man] Yeah, the beeping noise
is always when I intervene.

[narrator] The scanners
are picking up overgrown weeds.

The car has some problems
at the intersection here.

[narrator] MIG thinks
they're obstacles,

so it brakes for them.

Aside from that, they think
MIG is performing pretty well.

[car horn beeps]

-Hey, we're autonomous, buddy!
-[laughs]

[narrator] Ah, well
enough for today's big test.

[Dan] Let's take it up a notch.

We are going to do autonomous
driving, on the Autobahn.

[researcher] Okay, Miao.

-Ready.
-Oh God! Okay, there.

-That's autonomous now?
-Yeah, now it is autonomous.

Okay I take my foot off
and now the car takes over.

Whoa!

And now the car follows
the car in front of us

so I don't do anything.

So it knows where that car
in front of us is

and it just follows it?

[man] Yeah, it follows
everything on its lanes.

So you guys are totally calm
right now?

Well, we are alert,
but we check

if other cars
Might cut our lanes.

And how's everything look
on the computer?

It's good. All the sensors
are up and running.

We drive pretty smoothly
on Autobahn.

It checks the velocity
of the car in front of us,

and the distance, and from
these two parameters

it calculates the speed
it wants to go.

[narrator] We're traveling
at today's specified top speed.

Maybe you can try
an overtaking maneuver now.

So maybe you try you can try
an overtaking maneuver,

but I think there are
a lot of cars behind us.

Maybe you could
slow down to 90.

[narrator] Now I'm
really worried.

They want MIG to overtake
the car in front of us.

It's driven
by one of their colleagues.

When he slows down,
MIG will decide

whether it's safe to pass him,
or not.

That's what scares me.

Cars come up very quickly
in the passing lane

It's not safe, there are
a lot of cars back there!

And does it ask permission,
or does it just do it?

-It just does it.
-Oh my goodness!

[narrator] The car
in front slows.

MIG finds a gap
in the traffic,

and goes for it.

Daniel intervenes because
he can't see the gap.

No, this is too dangerous.

I mean, they come
at a hundred kilometers.

[narrator] They try again.

Okay, we are in
autonomous mode again.

[indistinct voice on radio]

[narrator] The car in front
slows. MIG hits the gas.

Okay, now we overtake.

-[Dan] Wow, that's real.
-[man] Yeah.

Wow!

[narrator] MIG passes
the passing test.

Not once, but several times.

There's still more work
to be done.

But it's a start down the road
of driverless cars.

That was a bit of a crazy ride!
Thanks again guys!

[car horn beeps]

Finally, as if that wasn't
thrilling enough!

We're airborne
for our final story.

But there's no aircraft
in sight.

In fact, we're even staying
indoors... skydiving!

In the world's largest
vertical wind tunnel!

[rock music]

[man] Most people see it as
a bucket list kind of thing.

Everyone wants to do it
once in their life.

[narrator] A giant
leap of faith...

begins right here.

[crowd cheers]

[narrator] It's skydiving's
inside secret.

What you learn in the tunnel
you can take to the sky.

[narrator] Paraclete XP,

the biggest vertical
wind tunnel on the planet,

in Raeford, North Carolina.

-It's addictive.
-It is addictive!

I want to do it again.
[laughs]

[narrator] And while families
like this one get sucked

into the excitement in this
five meter windy playground,

Every time she comes
here she has to do it!

there are some other clients
who take things

a little more seriously.

The fact that you can get
in the tunnel,

for two, even four minutes
at a time, come back out,

watch exactly what you did,
debrief it,

and get right back in.

It's unparalleled to be able to
actually jump out of a plane,

pack, repack again,
go back over it,

and the exhaustion factor
comes in to play as well,

so this is an awesome
opportunity to have this

local here to Fort Bragg.

[narrator] These are
the Golden Knights,

the US Army's high-flying
goodwill ambassadors.

[together] Out the hole,
into the black.

Once you're there, you never go
back. Boom! The Golden Knights.

Drafted from military ranks,

they are like
the parachuting elite.

Today, the Golden Knights
are training.

With the sound of the bell,
they dive right in.

Today we're just going to be
working on making points

and being able to fly your
body in, next to somebody.

[narrator] Not an easy feat.

The wind speed in here
can simulate skydiving

at over 180 miles per hour.

Every flight can be customized
in this control room.

Two-thousand horsepower fans

push hot air out
past exterior louvers.

New air flows down and into
the chamber, where it is spun

around by turn levers, making
it virtually turbulence free.

You realize little things
make a huge difference,

like your hand corking
a little bit one way,

or your foot
turning out another,

and our boss can get in there,
tell us what we're doing

wrong or right, and we execute
it and make a difference.

[narrator] Much better
to make mistakes in here

than in the skies.

Still, it's dangerous.

A collision at this speed
could cause serious injury.

Sometimes you have your day,
sometimes you don't.

It's like any other sport
in the world.

[narrator] A sport that
sparks wonder at airshows

and inspires others to fly.

[man] There's nothing like it
in the world.

Absolutely nothing.

People ride planes every day,
but how many people

can get out of a plane
and just fall all on their own?

It's awesome.

[narrator] Awesome enough
that this family

is getting a jump start.

Anybody can do it.
Whether you're a kid, or 60,

or a grandparent,
a mom, a dad, doesn't matter.

So it's really cool.

Wow, what a great way
of experiencing

non-stop sky diving without
the fear of jumping

out of a plane.

Well, that's all we've got
time for today.

Thank you very much for
watching How Tech Works.

Until next time,
me, Dr. Basil Singer!

[ending music]