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Tonight, we'll be assembling the world's
greatest robot orchestra and explaining
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how simple motors will allow these
machines to perform alongside human
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musicians. Welcome to the Christmas
Lecture.
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A robot.
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Automated machines that use simple
motors and clever software to copy the
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done by humans.
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And they're getting smarter all the
time.
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Take a look at these little fellas here.
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Robotic acrobat that can balance on a
tight rope.
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Or our six -legged robot spider here
that can shift its weight to stay
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upright.
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Just like a human can.
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But what about something slightly more
complicated?
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What about a musical instrument?
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I could do this, but I don't think you
can do this.
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Well, we'll see if you can do it later
on. Let's see.
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Now, if you've seen any of my earlier
lectures, you'll know that I've been
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setting myself a grand challenge each
time. And tonight is no different.
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The first person to achieve continuous
movement with electricity and
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the first electric motor, which is
essential for all robots to function,
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Royal Institution's very own Michael
Faraday.
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Now, he was fascinated with the
relationship between electricity and
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And tonight, I want to honour his work.
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So let's do something amazing with
motors that Michael Faraday could never
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imagined in 1821.
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So drum roll, please.
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Very good.
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Tonight, we are going to construct the
world's greatest robot orchestra.
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Now, the sound of an orchestra playing
in perfect harmony, to me...
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represents the pinnacle of human
achievement.
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So the question is, can robots replicate
this?
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Over the past few months, engineers from
across Europe have been building robot
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musicians.
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And tonight, we've set them the ultimate
challenge to play the Doctor Who theme
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tune.
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Now, some members of our ensemble have
used hack technology from around the
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to make the music.
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Others have programmed and trained to
play much more traditional instruments.
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And they'll all be accompanied by real
living members of the London
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Orchestra.
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Honestly, this truly is going to be
great.
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So let's break down our problem into
steps to build up our orchestra.
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We need to break down the tune into its
components for the Doctor Who theme
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tune. So first thing we need is the
rhythm section, the drums.
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Then we need that low bass synth sound,
so we need some synthesizers.
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Then let's add some guitars into that.
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But then we need the melody for our
Doctor Who theme tune.
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And we also need a keyboard in the tune.
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And then, for a bit of fun, let's make
one of our instruments fly.
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Now, one thing all of these robots have
in common is that they'll all be relying
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on the simple relationship between
electricity, magnetism, and movement. So
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that's where I'm going to start.
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This is the world's first motor.
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And it was demonstrated in this lecture
theatre by...
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michael faraday over 200 years ago and
charlotte who is the curator of
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collections at the ri has very kindly
brought this in for us now it's so
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that nobody's allowed to touch it apart
from charlotte so thank you very much
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for bringing this in charlotte so andy
has very kindly built a replica for us
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well
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Now, Faraday knew that if he could run a
current through a wire, this would
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create a magnetic field around that
wire.
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So if we place the wire next to the
magnet with a magnetic field running
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perpendicular or at right angles to the
one created around the wire, the wire
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would move.
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But the movement would break the
circuit, so we couldn't really get
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movement until he remembered Mercury.
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But before we get this mercury out, I
think we should get the real fragile one
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out of the way. So thank you very much,
Charlotte.
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Now, Andy's going to pour the mercury
around the magnet.
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Then we can dip this metal needle that
Andy has here into the mercury.
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and we can pass an electric current
through it.
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So we can just use a normal power supply
to pass the electric current through
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it.
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And then what we should see is rotation.
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So the mercury metal conducts
electricity, but it also allows the
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which at room temperature, the mercury
is a liquid, So the objects can move
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freely through that.
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And there we are. We have rotation.
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And it just keeps moving round and round
because there is liquid in there which
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allows that continuous movement.
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But of course, in modern motors, we use
brushes instead of that mercury.
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But thank you very much for your help
there, Andy.
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Now, most of us still work on this
principle, and you can even try building
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yourself.
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You can make one actually out of a
battery, a magnet, and a coil of wire.
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And I'm going to come and sit next to
you, if that's all right, to come and do
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this. So shift you along, everybody.
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That's enough, I'm not that big.
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Okay, now this is a really simple one
that you're going to help me with. Okay,
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so what's your name? Lucy. Lucy, okay.
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So what we have here, Lucy, is a
battery.
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a magnet and a coil, nice and simple.
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So what I want you to do is just put
that battery on top of that magnet.
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Okay, you see it's a very strong magnet.
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So that magnet can set up a magnetic
field.
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Then we have our coil here, and if we
place our coil over the top
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of that battery, it will generate a
current, an electrical current through
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coil.
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So the wire sets off a separate magnetic
field, which runs perpendicular, or at
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right angles, to our magnetic field
here.
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And the result is that the two fields
react with each other, and our coil
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rotates.
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Okay? Got it, Lucy?
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So, place our coil over the top. There
we are.
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Then it goes round nice and fast.
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Thank you.
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In a moment, I'm going to be introducing
you to the first robot in our
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orchestra. But just before I do, I want
to show you a hack that we did with the
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most common robot of them all.
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Now, you might not think your washing
machine is a robot.
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But actually, it's just a collection of
motors that replicates the manual work
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of having to wash your clothes by hand.
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So on a much more basic level, it turns
electricity into movement.
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So if it's possible to turn electricity
into movement, can we turn movement into
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electricity?
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Well, a few weeks ago, I challenged Andy
to build a wind turbine and generate
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electricity using an old washing
machine.
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Now, this isn't as stupid as it sounds.
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When you put your power into your
washing machine, you get movement. The
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spins. So if you spin the drum...
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Surely you can get power out.
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So, Andy, how did you get on?
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Not too bad, not too bad. I didn't use
too many of the bits of the washing
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machine in the turbine, as you can see,
littered around here. But the main bit,
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obviously, is the motor. This is the
main motor that turns the drum in the
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washing machine.
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And like you said, if we can use
something else to turn the motor, it
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generate electricity. So we're going to
be trying to use these turbine blades to
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turn the motor.
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to try and generate some electricity.
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Okay, how much electricity?
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Maybe not all that much. This probably
isn't the most efficient way to generate
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electricity in the world, but we should
be able to get some light out of these
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torches on the front here. Right, okay,
so these we need to keep an eye out, is
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it? Right, so we need to test it.
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Now, of course, it doesn't get that
windy in the lecture theatre, so Andy,
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conveniently, has brought his leaf
blower with him.
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So it might get a bit blustery over
here, so hang on to your heads,
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Okay, so are we ready?
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So everybody keep an eye out on those
lights.
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So let's test it, Andy. Okay.
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spinning, and the lights came on. So we
made a wind turbine from a washing
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machine. Now, as Andy said, it's not the
most efficient way to power your home,
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but it does show that relationship
between electricity, magnetism, and
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really well. Excellent work, Andy. Thank
you very much.
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A little bit more about motors. We can
start assembling our robot musicians.
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So let's start simple with the drums.
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Well, maybe not so simple, but you only
have to worry about the rhythm because
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on the drums the pitch doesn't change.
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So all we really need is a single motor
to play each drum, like this snare drum.
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So attached to each drumstick is a motor
that will connect the circuit so that
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the motor makes the stick hit the drum.
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And bounce back again. So I should be
able to just keep hitting that drum with
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every signal.
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Like so.
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Brilliant.
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But our orchestra isn't going to work by
me standing here pressing a switch. So
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we need to program that tune.
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For a human orchestra, we'd use sheet
music.
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Which has a line for the bass.
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The synth and the strings and of course
one for the drums as well.
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Now sheet music is similar actually to a
computer program in that it tells the
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musicians what notes to play, how long
to hold each note and how long they
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should play it for.
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Now let me show you a robot that uses
some very simple instructions to do
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something very, very cool.
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Remember these?
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Has anyone ever tried solving a Rubik's
Cube?
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Oh, lots of people.
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There you are then. You can have that
one. Try solving that.
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And someone over here, you try solving
that one.
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I need this one, I'm afraid.
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Okay, now, you should have solved it by
now, yes? How are you getting on?
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No? Not quite?
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Okay, well, keep going.
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Now it might seem impossible to solve,
but mathematicians have shown that you
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can solve any cube within just 20 moves.
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Because there's a certain pattern of
twists and turns that would get the cube
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back to normal. So all of the colours on
the side would be the same.
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Now the inventors of this robot set
themselves a challenge.
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This is CubeStormer 3.
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And it's the quickest cube solver in the
world.
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So how long do you think it would take
to solve this?
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How long?
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10 or 20 seconds.
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Yep, any advance?
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10, 20 to 30 seconds.
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Okay, well, let's see.
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I just align my Rubik's Cube.
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And if Dave, you just want to come and
have a look at this.
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I press my go button.
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Wow.
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Four seconds.
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I know it looks magic, but actually it's
Lego and a smartphone.
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Now it takes photographs of the cube.
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And the software works out the quickest
way in which to solve these Rubik's
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Cubes. So it writes a program to tell
each robot arm which way to turn.
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00:14:53,040 --> 00:14:56,919
And then actually, once the math is
done, it's just a simple list of
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instructions. So spin this part of the
cube, rotate that part, spin the other
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face.
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Now the same is true for our robot
drummer.
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Now he's from Queen Mary's University of
London, and here he is.
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Say hi to Motima.
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Hi, Motorman.
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Hi.
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Now, we need to write a program to know
exactly when each motor will turn on to
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create the rhythm.
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Now, the easiest way to do this is a
form of electronic sheet music called
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or Musical Instrument Digital Interface.
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And it's been designed specifically so
that instruments can talk to the
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and back again.
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So, instead of writing a whole new
program,
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we can take the drum from our sheet
music, write it in MIDI software, which
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then convert it into instructions for
Mortimer.
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So if we sent a simple code to the
drummer, we should hear this.
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Okay, nice and simple.
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But we could send a more complex code
that repeats a certain rhythm, and we'd
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hear this.
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Excellent. Okay, already we're starting
to rock and we just have one.
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Now, in fact, all our robots are going
to be controlled by MIDI, as it means we
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can work in a format that humans can
read, which is sheet music, and then
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convert it straight into code that our
robot musicians are much more
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with.
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Okay, so one musician down, lots more to
go.
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Because we don't just need a rhythm in
our piece.
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We also need pitch.
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So we need to start with that low bass
synthesizer sound.
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You know the one for Doctor Who? Who
knows it?
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Sing it, everybody.
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Not bad, not bad. I hope the robot
orchestra are as good as you guys.
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So, we need another robot that can read
music and adjust the pitch of the sound
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as it produces it.
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Now, in the spirit of making and hacking
and repurposing, this robot musician is
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00:17:26,829 --> 00:17:30,250
made from a device that was made
redundant many years ago.
235
00:17:30,890 --> 00:17:35,949
Now, in the days before laser and inject
printers, documents were printed by
236
00:17:35,950 --> 00:17:38,250
very noisy dot matrix printers.
237
00:17:39,110 --> 00:17:43,530
which had to punch a letter shape
through the ink -covered ribbon onto
238
00:17:44,590 --> 00:17:49,929
Now, we don't really think about
printers as robots, but they use motors
239
00:17:49,930 --> 00:17:54,570
replicate human work, or at least the
hundreds of monks that used to copy
240
00:17:56,410 --> 00:18:01,849
So, if we set it printing, we'll hear
the motors whirring away and changing
241
00:18:01,850 --> 00:18:05,170
pitch. But we're not interested in
what's being printed.
242
00:18:05,390 --> 00:18:07,710
We just want to hear how the sound
changes.
243
00:18:08,780 --> 00:18:13,879
So the owner of this has hacked it, and
he realized that he could alter the
244
00:18:13,880 --> 00:18:16,580
pitch of the sound by printing different
patterns.
245
00:18:17,320 --> 00:18:19,980
So it accepts our MIDI code.
246
00:18:20,320 --> 00:18:25,639
So the computer in the printer converts
into instructions telling different
247
00:18:25,640 --> 00:18:27,060
motors when to move.
248
00:18:27,740 --> 00:18:31,420
So it sounds like this. Let's see if you
can guess the tune.
249
00:18:52,040 --> 00:18:53,090
Anyone guess it?
250
00:18:55,420 --> 00:18:56,500
Anyone guess it?
251
00:18:57,420 --> 00:18:58,470
Yeah.
252
00:18:58,740 --> 00:19:03,080
Oh, to joy. Well done, yes. And well
done if you knew that at home as well.
253
00:19:03,320 --> 00:19:05,880
Now, our orchestra is starting to take
shape.
254
00:19:06,600 --> 00:19:10,000
Robots can convert MIDI into motorized
movement.
255
00:19:11,380 --> 00:19:15,419
And there's a much more sophisticated
breed of printer that's starting to
256
00:19:15,420 --> 00:19:16,620
increase in popularity.
257
00:19:17,260 --> 00:19:21,860
and may prove very useful as we move to
the next instrument in our orchestra.
258
00:19:23,660 --> 00:19:28,779
Finishing off the rhythm section of our
unconventional orchestra is a bass
259
00:19:28,780 --> 00:19:34,479
guitar, which has been adapted to play
itself for students at the University of
260
00:19:34,480 --> 00:19:35,530
Leeds.
261
00:19:35,740 --> 00:19:41,439
So like our earlier instruments, it
reads our MIDI program, but this uses
262
00:19:41,440 --> 00:19:45,520
solenoids and compressed air to press
down on the strings.
263
00:19:46,380 --> 00:19:52,099
And then it adjusts the pitch of the
notes played when the actuator plucks
264
00:19:52,100 --> 00:19:54,800
strings. So just like a human guitarist
would.
265
00:19:55,380 --> 00:19:58,840
So let's hear what our bass guitar
sounds like.
266
00:20:11,460 --> 00:20:12,510
Wow.
267
00:20:13,740 --> 00:20:14,790
Whoa.
268
00:20:21,100 --> 00:20:25,059
The team who put this together wanted to
give the guitar an even more human
269
00:20:25,060 --> 00:20:28,120
-like feeling, so it gave it fingers.
270
00:20:30,660 --> 00:20:37,659
Now, the solution for these fingers was
to print them using a 3D printer, which
271
00:20:37,660 --> 00:20:40,420
is quite similar to this one that we
have.
272
00:20:41,900 --> 00:20:46,119
Now, we have to be very careful with
this because it's halfway through making
273
00:20:46,120 --> 00:20:47,170
model.
274
00:20:49,580 --> 00:20:55,240
And it's making a model of someone in
the audience.
275
00:20:55,760 --> 00:20:58,400
So Isla, would you like to come and join
me?
276
00:21:02,160 --> 00:21:04,380
Hi, Isla. How are you?
277
00:21:06,860 --> 00:21:11,140
Okay, so let's just go around here so we
can see what's going on, Isla.
278
00:21:11,380 --> 00:21:17,339
So a few weeks ago, we sent some people
to Isla's house to get a 3D scan of her
279
00:21:17,340 --> 00:21:18,390
head.
280
00:21:19,210 --> 00:21:24,689
And now, we can see people scanning your
head there. That must have been very
281
00:21:24,690 --> 00:21:26,370
strange for your Isla, wasn't it?
282
00:21:28,410 --> 00:21:33,910
So, the head is being printed layer by
layer.
283
00:21:34,210 --> 00:21:39,309
So, each of these layers can be seen as
a thinly sliced horizontal cross
284
00:21:39,310 --> 00:21:41,450
-section of Isla's head.
285
00:21:42,070 --> 00:21:47,909
Now, 3D printing is just a rapid
prototyping process, which is capable of
286
00:21:47,910 --> 00:21:52,080
making... three -dimensional solid
objects from a digital file.
287
00:21:53,220 --> 00:21:56,200
Now, to buy a 3D printer is actually
still quite expensive.
288
00:21:56,800 --> 00:22:00,859
But if you have a design, there are
companies that will print one for you,
289
00:22:00,860 --> 00:22:03,210
in the same way people print your
photographs.
290
00:22:03,280 --> 00:22:08,279
So, as you can see, this would take a
very long time to start printing Isla's
291
00:22:08,280 --> 00:22:09,099
head now.
292
00:22:09,100 --> 00:22:11,680
So we have printed one a little earlier.
293
00:22:12,120 --> 00:22:13,680
So are you ready for this, Isla?
294
00:22:16,660 --> 00:22:17,710
Wow!
295
00:22:18,060 --> 00:22:19,260
What do you think, Isla?
296
00:22:26,140 --> 00:22:33,059
I think that looks great. What do
297
00:22:33,060 --> 00:22:34,110
you think, Isla?
298
00:22:34,180 --> 00:22:35,480
I think it's good.
299
00:22:35,481 --> 00:22:39,079
It looks fantastic. I did have my hair
up at the time. You did have a ponytail
300
00:22:39,080 --> 00:22:40,460
in at the time, did you? Good.
301
00:22:40,461 --> 00:22:41,799
We're glad.
302
00:22:41,800 --> 00:22:46,300
Well, the extra special thing here is
that your book...
303
00:22:46,560 --> 00:22:51,219
is going to go into the Royal
Institution downstairs next to Michael
304
00:22:51,220 --> 00:22:52,980
bus. How good is that?
305
00:22:53,960 --> 00:22:55,500
Okay. I'm done.
306
00:22:57,360 --> 00:22:59,400
All right. Thank you very much, Alan.
307
00:22:59,620 --> 00:23:00,670
Thank you.
308
00:23:03,480 --> 00:23:09,199
Now, printing colourful fingers is fun
for our bass guitar, but is there a more
309
00:23:09,200 --> 00:23:11,680
serious application for our 3D printing?
310
00:23:12,560 --> 00:23:13,610
Well, yes.
311
00:23:14,120 --> 00:23:18,520
And hopefully, we have a video call here
with Hayley Fraser in Inverness.
312
00:23:18,940 --> 00:23:20,400
Now, hi, Hayley.
313
00:23:20,620 --> 00:23:21,670
How are you?
314
00:23:22,520 --> 00:23:28,879
Hi. Good, good. Now, Hayley, I
understand you have a prosthetic hand
315
00:23:28,880 --> 00:23:30,320
3D printed. Is that right?
316
00:23:31,080 --> 00:23:33,600
Yeah. Yeah? And can you show us it?
317
00:23:35,680 --> 00:23:36,730
Fantastic.
318
00:23:36,960 --> 00:23:38,340
Do you want to give us a wave?
319
00:23:40,830 --> 00:23:45,150
That's brilliant. Now, this must be life
-changing for you, is it?
320
00:23:45,990 --> 00:23:47,040
Yeah.
321
00:23:48,170 --> 00:23:52,390
I really like the colour, Hayley, the
pink colour. Did you choose that?
322
00:23:52,850 --> 00:23:55,030
Yes. You did, yes.
323
00:23:55,270 --> 00:24:00,810
OK. Now, can you show us something with
the hand? Maybe pick something up.
324
00:24:03,830 --> 00:24:10,209
So, Hayley's dad... When did Hayley get
this
325
00:24:10,210 --> 00:24:14,330
hand? Hayley received it back in June
this year.
326
00:24:14,730 --> 00:24:20,269
It took around six weeks for the whole
process, which was a very quick
327
00:24:20,270 --> 00:24:22,050
turnaround. Wow, that's amazing.
328
00:24:22,330 --> 00:24:25,510
It must have made Hayley's life just so
different, did it?
329
00:24:25,970 --> 00:24:27,510
Oh, yes, right on out, yeah.
330
00:24:27,850 --> 00:24:32,809
Yeah. I mean, I think the thing that
really impresses me most about this is
331
00:24:32,810 --> 00:24:36,950
prosthetic hands can cost literally
thousands of pounds.
332
00:24:37,760 --> 00:24:43,479
But this one is so low cost that it
means that as Hayley grows, then the
333
00:24:43,480 --> 00:24:46,040
can always be the right size for Hayley
as well.
334
00:24:46,560 --> 00:24:50,140
Yeah. And that must be life -changing in
itself.
335
00:24:50,700 --> 00:24:56,019
Yeah, of course. We can actually buy 3D
printers for our home, which we can
336
00:24:56,020 --> 00:24:58,560
actually print the parts for ourselves.
337
00:24:58,780 --> 00:25:02,480
That's fantastic. So you can actually
print your own hands at home then as
338
00:25:02,940 --> 00:25:06,660
Yes. So it means you can choose what
colour you want as well, Hayley.
339
00:25:08,060 --> 00:25:09,240
Yes, that's great.
340
00:25:09,580 --> 00:25:13,220
OK, well, thank you very much for
joining us and happy holidays to you.
341
00:25:13,460 --> 00:25:15,390
Thank you very much. Thank you. Bye
-bye.
342
00:25:22,300 --> 00:25:25,340
Now, our orchestra is starting to take
shape.
343
00:25:25,820 --> 00:25:32,299
We can have a drummer, a bassist and a
printer. Let's not forget our lovely
344
00:25:32,300 --> 00:25:33,350
printer.
345
00:25:33,870 --> 00:25:38,029
While these robot musicians will get
away with playing the right notes in the
346
00:25:38,030 --> 00:25:42,410
right order, some instruments are much,
much harder to play.
347
00:25:43,310 --> 00:25:48,789
Now, we want a robot to play the solo
part in Doctor Who. Who knows the solo
348
00:25:48,790 --> 00:25:49,840
part in Doctor Who?
349
00:25:50,270 --> 00:25:51,320
Sing it.
350
00:25:53,970 --> 00:25:57,290
Someone down here is very, very good.
351
00:25:58,270 --> 00:25:59,320
Excellent.
352
00:26:00,360 --> 00:26:03,550
If it all goes wrong later, I might just
get you to do that, okay?
353
00:26:04,680 --> 00:26:10,419
Now, we want them to play it on one of
these, a theremin. And they are
354
00:26:10,420 --> 00:26:12,240
notoriously difficult to play.
355
00:26:13,460 --> 00:26:16,900
Because you have to play in mid -air.
356
00:26:19,860 --> 00:26:23,620
So you can hear some sort of strange
noise.
357
00:26:24,160 --> 00:26:27,940
And on the left hand, I can control the
volume.
358
00:26:30,860 --> 00:26:33,860
And then my right hand can control the
pitch.
359
00:26:45,051 --> 00:26:51,799
Well, I've definitely not perfected it
yet, so I hope the robot does a lot
360
00:26:51,800 --> 00:26:52,850
better than me.
361
00:26:53,550 --> 00:26:57,769
One of the things that makes this
especially hard to play is that to keep
362
00:26:57,770 --> 00:27:02,310
tune, you have to position your hands in
exactly the right place in the air.
363
00:27:02,990 --> 00:27:06,929
If the theremin is nudged or the
settings are different, you'd have to
364
00:27:06,930 --> 00:27:08,070
reposition your hands.
365
00:27:08,810 --> 00:27:13,229
So you have to listen to the sound
that's being produced, think whether
366
00:27:13,230 --> 00:27:18,229
tune, and then think, do I need the
pitch higher or lower, and then move
367
00:27:18,230 --> 00:27:19,280
hands accordingly.
368
00:27:19,790 --> 00:27:22,130
Now this is called a feedback loop.
369
00:27:22,590 --> 00:27:25,970
And this is what our theremin -playing
robot will need to master.
370
00:27:27,170 --> 00:27:33,329
Now, to show you what I mean about a
feedback loop, I need a volunteer to
371
00:27:33,330 --> 00:27:35,270
me with the 20 whistle.
372
00:27:37,450 --> 00:27:41,330
Okay, you there with the necklace on?
Yeah, okay, come down.
373
00:27:47,850 --> 00:27:50,390
Let's see. Okay, let's see. Right.
374
00:27:50,391 --> 00:27:53,069
What I want you to do, here's your
swanee whistle.
375
00:27:53,070 --> 00:27:56,130
I'm going to turn away from you and play
a note.
376
00:27:56,510 --> 00:27:59,330
And then I want you to try and replicate
that note.
377
00:27:59,870 --> 00:28:00,920
Okay?
378
00:28:05,930 --> 00:28:06,980
Got it?
379
00:28:10,470 --> 00:28:11,520
Keep going.
380
00:28:29,480 --> 00:28:31,890
Oh, I think you've just about got it
there, yeah.
381
00:28:31,940 --> 00:28:33,740
But it's quite difficult, isn't it?
382
00:28:33,940 --> 00:28:36,890
But actually what you were doing there
was a feedback loop.
383
00:28:37,160 --> 00:28:42,479
So I gave you a note, you were trying to
listen to what that note was, and then
384
00:28:42,480 --> 00:28:48,339
you were adjusting your hands and the
sound accordingly so you hit the same
385
00:28:48,340 --> 00:28:51,839
as me. But it's quite difficult, isn't
it? Yeah, you did very well. Thank you
386
00:28:51,840 --> 00:28:52,890
very much.
387
00:28:58,920 --> 00:29:05,719
Now this rather cute little robot is
programmed to follow a very simple
388
00:29:05,720 --> 00:29:06,770
loop.
389
00:29:07,380 --> 00:29:13,680
So when I set it running, what we need
is for it to follow a white line.
390
00:29:14,100 --> 00:29:19,020
So we just have some white line on a
tape around the theatre.
391
00:29:20,120 --> 00:29:23,140
Now the program we've written is a nice
simple one.
392
00:29:23,360 --> 00:29:26,920
So if I set this running on the line,
393
00:29:35,880 --> 00:29:37,280
we can see it start to move.
394
00:29:37,640 --> 00:29:40,480
So the program is written. It's very
simple.
395
00:29:41,280 --> 00:29:45,240
At the front of that robot is an
infrared light and a sensor.
396
00:29:46,040 --> 00:29:50,819
Now, when the light flashes, the amount
of light reflected back is measured by
397
00:29:50,820 --> 00:29:51,870
that sensor.
398
00:29:51,940 --> 00:29:56,739
So if the sensor is over the white line,
there's a high value, and the computer
399
00:29:56,740 --> 00:29:59,580
tells the motor to move the robot
forward.
400
00:30:00,500 --> 00:30:04,640
If it's over the black, the amount of
light reflected is too low.
401
00:30:05,130 --> 00:30:10,849
So the computer tells the motors to move
the robot left or right and find that
402
00:30:10,850 --> 00:30:11,900
white line again.
403
00:30:12,470 --> 00:30:15,010
And each of these is a feedback loop.
404
00:30:16,050 --> 00:30:17,250
We have an action.
405
00:30:17,670 --> 00:30:18,790
The robot moves.
406
00:30:19,830 --> 00:30:21,750
There's a measurement with the sensor.
407
00:30:22,070 --> 00:30:26,090
The robot reacts and it changes what
it's doing.
408
00:30:26,570 --> 00:30:31,729
And you can even see it's just gone
round a little corner there. So I think
409
00:30:31,730 --> 00:30:32,949
might just let it keep going.
410
00:30:32,950 --> 00:30:34,000
What do you think?
411
00:30:34,370 --> 00:30:35,750
Let's see how far it goes.
412
00:30:36,610 --> 00:30:41,009
Okay, well, we've got a camera mounted
to the front of it, so we'll just follow
413
00:30:41,010 --> 00:30:43,750
its progress and we'll pick up with it
later on.
414
00:30:45,410 --> 00:30:51,149
Now, our more advanced robot, like the
one capable of playing a theremin, can't
415
00:30:51,150 --> 00:30:53,150
really be programmed in this way.
416
00:30:53,830 --> 00:30:59,229
Our little line -following robot knows
what it's likely to encounter, so we can
417
00:30:59,230 --> 00:31:01,130
tell it exactly how to react.
418
00:31:02,220 --> 00:31:08,879
But what happens if you place a robot in
an unpredictable alien world without a
419
00:31:08,880 --> 00:31:10,200
big white line to follow?
420
00:31:10,640 --> 00:31:16,199
In a place where communication is almost
impossible and robots have to deal with
421
00:31:16,200 --> 00:31:17,580
the challenges themselves.
422
00:31:18,660 --> 00:31:21,840
So on the surface of Mars, for example.
423
00:31:22,860 --> 00:31:27,940
So please give a very warm welcome to
Abby Hutty and Bruno.
424
00:31:40,500 --> 00:31:46,899
So, Abby, you've heard about our
challenge to make a most advanced robot
425
00:31:46,900 --> 00:31:51,559
theremin. Now, you're part of a team
that's building a much, much more
426
00:31:51,560 --> 00:31:52,610
complicated robot.
427
00:31:52,660 --> 00:31:53,960
So, what do we have here?
428
00:31:54,240 --> 00:31:59,400
This is Bruno. This is one of our
prototype rovers for the 2018 Mars
429
00:31:59,500 --> 00:32:03,580
that's the European Space Agency's first
rover mission to Mars.
430
00:32:03,581 --> 00:32:07,889
So Bruno here's a prototype, so that
means he's a working model, and he helps
431
00:32:07,890 --> 00:32:11,529
to develop things like how we're going
to drive around on Mars, and also how
432
00:32:11,530 --> 00:32:15,309
we're going to actually autonomously
navigate, so how we're going to work out
433
00:32:15,310 --> 00:32:17,389
where we want to travel when we're on
Mars.
434
00:32:17,390 --> 00:32:22,069
Fantastic. Now, I know tonight that Paul
is actually controlling him for us in
435
00:32:22,070 --> 00:32:25,149
the lecture theatre, but I'm guessing
that's not what's going to happen when
436
00:32:25,150 --> 00:32:25,949
he's on Mars.
437
00:32:25,950 --> 00:32:29,549
Yeah, so in the lecture theatre it's
pretty dark in here, and the rover is
438
00:32:29,550 --> 00:32:30,810
designed to be able to see...
439
00:32:31,230 --> 00:32:34,300
and get the right kind of contrast on
Mars during the daytime.
440
00:32:34,350 --> 00:32:37,370
So he can't really work out things in
the dark.
441
00:32:37,590 --> 00:32:40,930
So we're actually having to control him
by Wi -Fi, which is great.
442
00:32:40,931 --> 00:32:43,929
We're just remote controlling him, but
we can't do that when we're on Mars
443
00:32:43,930 --> 00:32:48,509
because Mars is so far away that it
would take up to 22 minutes for the
444
00:32:48,510 --> 00:32:52,569
to get there just to tell them what to
do. So if you're driving around on Mars
445
00:32:52,570 --> 00:32:53,890
and you hit the stop button...
446
00:32:53,891 --> 00:32:55,449
That's a bit too long, really.
447
00:32:55,450 --> 00:32:59,389
So we have to make our rover intelligent
enough to make its own decisions about
448
00:32:59,390 --> 00:33:02,269
what it can and can't do safely and
drive around all by itself.
449
00:33:02,270 --> 00:33:05,529
Brilliant. So you're almost like giving
it coordinates that you might give a car
450
00:33:05,530 --> 00:33:08,969
GPS? Yeah, it's a bit like that. We can
give it a destination that it's got to
451
00:33:08,970 --> 00:33:13,389
go to. It can be up to two days' drive,
and it'll just look at what's in front
452
00:33:13,390 --> 00:33:17,609
of it. It can bring up an elevation map,
which is basically a picture of what's
453
00:33:17,610 --> 00:33:19,290
in front of it in three dimensions.
454
00:33:19,450 --> 00:33:21,930
And then it can do calculations to work
out...
455
00:33:21,931 --> 00:33:26,009
what's too big an obstacle to climb over
and what's safe for it to trundle over
456
00:33:26,010 --> 00:33:30,829
and then just pick its own route to that
destination, phone us up. I think we
457
00:33:30,830 --> 00:33:34,769
have that here, yeah. So this is an
elevation map. So this shows us there's
458
00:33:34,770 --> 00:33:38,469
big rock in front of us here that would
be too big to climb over, but all of the
459
00:33:38,470 --> 00:33:40,150
blue area, that's nice and safe.
460
00:33:40,151 --> 00:33:43,229
Nothing's too big, so we can just drive
straight over that.
461
00:33:43,230 --> 00:33:47,590
Right, okay. So the other thing I'm
noticing here, Abi, is that these
462
00:33:47,730 --> 00:33:51,230
they don't have the normal rubber on
them like you would on tyres.
463
00:33:51,760 --> 00:33:55,060
And so they're all metal, so they're
very noisy. Why is that?
464
00:33:55,320 --> 00:34:00,260
Okay, so the primary objective of the
rover mission is to look for life on
465
00:34:00,400 --> 00:34:02,820
either in the past or present living
life.
466
00:34:03,080 --> 00:34:06,040
And rubber comes from trees. It's a
natural substance.
467
00:34:06,380 --> 00:34:10,718
So if we were to take rubber tires with
us, that could contaminate the samples
468
00:34:10,719 --> 00:34:14,619
that we're looking at. And we could find
Earth life in that rubber and think
469
00:34:14,620 --> 00:34:15,760
that it was life on Mars.
470
00:34:15,761 --> 00:34:18,769
So we've got to make sure that nothing
that we take with us is going to
471
00:34:18,770 --> 00:34:23,029
contaminate Mars. We've got to develop
these flexible wheels so that you still
472
00:34:23,030 --> 00:34:26,669
get the same kind of traction and grip
going over rocks and going through sand
473
00:34:26,670 --> 00:34:28,169
as you would with a rubber tyre.
474
00:34:28,170 --> 00:34:32,269
but without anything organic inside it.
Wow, okay, that sounds like a tremendous
475
00:34:32,270 --> 00:34:33,320
project.
476
00:34:33,770 --> 00:34:39,129
Thank you. And all of this technology
that you're developing here will be on
477
00:34:39,130 --> 00:34:42,589
ExoMars rover, is that right?
Absolutely, yes. So we're developing
478
00:34:42,590 --> 00:34:46,289
bits and pieces, lots of different
prototypes that test different things,
479
00:34:46,290 --> 00:34:49,480
will all come together in our final
rover that launches in 2018.
480
00:34:49,481 --> 00:34:50,448
That's fantastic.
481
00:34:50,449 --> 00:34:54,209
Well, thank you so much, Abby, for
bringing this along, and the very best
482
00:34:54,210 --> 00:34:55,890
luck with this fantastic project.
483
00:34:56,170 --> 00:34:57,220
Thank you. Thank you.
484
00:35:07,180 --> 00:35:08,380
Absolutely incredible.
485
00:35:08,540 --> 00:35:14,039
And to play our theremin in our
orchestra, our robot will need the
486
00:35:14,040 --> 00:35:15,380
Bruno, that Mars rover.
487
00:35:16,200 --> 00:35:20,320
Because Abby didn't tell Bruno exactly
how to get to its destination.
488
00:35:20,880 --> 00:35:24,600
She just tells him where to go, and he
was working out the rest.
489
00:35:25,380 --> 00:35:30,699
So in the same way, we need to be able
to tell our theremin player which note
490
00:35:30,700 --> 00:35:34,400
hit, and it must make a judgment as to
what the note might be.
491
00:35:35,150 --> 00:35:39,489
Then it listens to the sound that's
being produced and makes adjustments to
492
00:35:39,490 --> 00:35:43,280
that perfect pitch, just as we were
doing with the swanny whistles earlier.
493
00:35:44,510 --> 00:35:46,930
And here is our solution.
494
00:35:48,250 --> 00:35:50,850
We're back with our H5W.
495
00:35:51,430 --> 00:35:54,230
And he's such a cute machine, isn't he?
496
00:35:54,870 --> 00:36:00,209
It's modelled on a three -year -old. And
it lives in Barcelona in Spain. And
497
00:36:00,210 --> 00:36:03,790
it's travelled here together with
several friends, including...
498
00:36:04,360 --> 00:36:10,219
Paul Frasier and Vicky Valutz from SPECS
Research Group at the Catalan Institute
499
00:36:10,220 --> 00:36:14,540
of Advanced Studies at the University
Pompidou Fabra.
500
00:36:15,220 --> 00:36:16,270
Welcome.
501
00:36:18,560 --> 00:36:19,680
Hi, it's IW.
502
00:36:24,480 --> 00:36:29,200
My name is H5W. I am like a robot.
503
00:36:29,840 --> 00:36:32,580
Paul is my friend and we love to be
here.
504
00:36:35,240 --> 00:36:39,060
Brilliant. Now, Paul, why would you need
such a complicated robot?
505
00:36:39,880 --> 00:36:45,160
Well, the iCub robot, this one called
H5W, has about 60 motors.
506
00:36:45,460 --> 00:36:47,750
Like many of the robots we saw can do
one thing.
507
00:36:47,751 --> 00:36:50,859
But if you look at their own bodies, we
can do more than one thing.
508
00:36:50,860 --> 00:36:55,739
On the other hand, if you now really
want to advance robots and make a robot
509
00:36:55,740 --> 00:37:00,689
that really can be our friend, that can
work with us and we can relate to, then
510
00:37:00,690 --> 00:37:04,309
we might have to think about giving them
more of the property that we have. And
511
00:37:04,310 --> 00:37:08,809
it does feel really human -like. When it
turns around and looks at you and winks
512
00:37:08,810 --> 00:37:13,629
at you and things, it does feel very,
very human -like. So let's see what it
513
00:37:13,630 --> 00:37:15,190
do with these hands.
514
00:37:15,490 --> 00:37:18,870
So H5W, can you do something?
515
00:37:20,690 --> 00:37:22,090
Let's play with the piano.
516
00:37:23,150 --> 00:37:24,530
That sounds like a good idea.
517
00:37:24,750 --> 00:37:26,390
Okay, so why don't you play a C?
518
00:37:26,630 --> 00:37:27,970
Can you play a C for us?
519
00:37:31,700 --> 00:37:35,339
Well, that was almost right. And we have
been practicing this the whole
520
00:37:35,340 --> 00:37:37,979
afternoon, you know, so I'm a little bit
disappointed.
521
00:37:37,980 --> 00:37:42,679
It's like a naughty three -year -old.
Look, H5W, can we try this again? And
522
00:37:42,680 --> 00:37:46,799
in mind, it's being recorded. Lots of
people are watching. Can you try to do
523
00:37:46,800 --> 00:37:47,850
right this time?
524
00:37:48,051 --> 00:37:50,039
Well done.
525
00:37:50,040 --> 00:37:51,220
Thank you very much.
526
00:38:00,460 --> 00:38:02,040
Yeah, I agree with that.
527
00:38:02,720 --> 00:38:07,219
So we've been talking about feedback
loops and how we need that for our
528
00:38:07,220 --> 00:38:12,879
orchestra. So this is a very
sophisticated feedback loop plus the one
529
00:38:12,880 --> 00:38:16,499
further from that as well, isn't it?
Well, this is the whole point. If you
530
00:38:16,500 --> 00:38:21,439
at our brain, it's actually managing
different kinds of feedback loops at the
531
00:38:21,440 --> 00:38:22,459
same time.
532
00:38:22,460 --> 00:38:25,760
You can think about brains like a
prediction machine.
533
00:38:25,761 --> 00:38:30,529
It's not only getting errors from the
world, as in the line -following robot,
534
00:38:30,530 --> 00:38:32,150
oh, I'm off, now I have to correct.
535
00:38:32,151 --> 00:38:33,589
It's like a feedback error.
536
00:38:33,590 --> 00:38:37,189
But it's really also predicting, like,
oh, what should the world look like when
537
00:38:37,190 --> 00:38:42,589
I'm doing things? So it's highly
relying, and on the same point as robot,
538
00:38:42,590 --> 00:38:45,029
predictions it's making about the world
it's in.
539
00:38:45,030 --> 00:38:48,870
And we'd need that if we were able to
coexist with robots as well. Absolutely.
540
00:38:48,871 --> 00:38:52,449
So we'd like to hear a tune from it. I
think we'd like to hear a tune, wouldn't
541
00:38:52,450 --> 00:38:53,500
we? Yeah?
542
00:38:54,310 --> 00:38:55,360
All right.
543
00:38:55,470 --> 00:38:56,730
Let's see what it can play.
544
00:38:57,370 --> 00:38:58,810
This is not really difficult.
545
00:38:59,790 --> 00:39:00,950
How about this?
546
00:39:22,611 --> 00:39:29,159
What do we think? I think that was
starting to sound like something. What
547
00:39:29,160 --> 00:39:30,210
think it was?
548
00:39:32,500 --> 00:39:36,040
Twinkle, twinkle, little star. It
sounded a bit like that, didn't it?
549
00:39:36,560 --> 00:39:37,720
Excellent. Correct.
550
00:39:38,480 --> 00:39:39,530
Well done.
551
00:39:40,420 --> 00:39:41,470
Correct. Well done.
552
00:39:42,020 --> 00:39:48,159
So it sounds like H5W could be the star
of our heroin playing later on. So thank
553
00:39:48,160 --> 00:39:52,120
you very much for showing this poll, and
thank you very much, H5W.
554
00:39:52,420 --> 00:39:53,470
Well done. Thank you.
555
00:40:01,800 --> 00:40:07,599
So I'm looking forward to hearing H5W
play our solo part on the theremin later
556
00:40:07,600 --> 00:40:08,650
on.
557
00:40:09,300 --> 00:40:15,379
Now, by using constant feedback loops,
we're now one step closer to completing
558
00:40:15,380 --> 00:40:16,430
our orchestra.
559
00:40:16,780 --> 00:40:20,320
So, how's our line following robot
getting on?
560
00:40:20,920 --> 00:40:24,170
Can we see any? Oh, yeah, we can see
some footage of him. Excellent.
561
00:40:24,171 --> 00:40:27,519
Okay, so you can see him actually going
around quite a tight corner there.
562
00:40:27,520 --> 00:40:31,079
That's quite difficult to do. So he's
definitely outside of the lecture
563
00:40:31,080 --> 00:40:32,960
and somewhere in the RI there, I think.
564
00:40:33,260 --> 00:40:37,859
But I think we should just put some tape
down outside the RI and just let him
565
00:40:37,860 --> 00:40:39,840
walk around London, see what's going on.
566
00:40:40,480 --> 00:40:46,260
Now, next, we want to work out how to
bring several robots to play together.
567
00:40:46,990 --> 00:40:50,490
After all, a good orchestra is much more
than the sum of its parts.
568
00:40:51,210 --> 00:40:57,529
Now, to give you an idea of how robots
work together, I want to introduce you
569
00:40:57,530 --> 00:40:59,310
a swarm of robots.
570
00:41:00,670 --> 00:41:06,509
These rather cute little things here are
pixel bots, and they're being developed
571
00:41:06,510 --> 00:41:09,330
by Disney Research and ETH Zurich.
572
00:41:09,870 --> 00:41:14,510
And they're tiny two -wheeled robots
that have LEDs.
573
00:41:15,210 --> 00:41:17,470
so that they can light up and make
shapes.
574
00:41:18,070 --> 00:41:23,010
So to tell me more about these, please
welcome developer Paul Beardsley.
575
00:41:27,570 --> 00:41:34,409
So thank you very much for joining us,
Paul. Now, these pixel bots have started
576
00:41:34,410 --> 00:41:39,189
swarming together in the middle, but
they're going to start a performance for
577
00:41:39,190 --> 00:41:40,690
us. I understand. Is that right?
578
00:41:40,890 --> 00:41:41,940
That's right.
579
00:41:41,990 --> 00:41:45,610
This is a swarm of robots that can make
images and animations.
580
00:41:46,130 --> 00:41:50,829
And what we're about to see is the story
of the universe as told by the pixel
581
00:41:50,830 --> 00:41:52,050
bots all in two minutes.
582
00:41:52,350 --> 00:41:57,109
Okay. So the way to think of it is each
robot is like one pixel, and what we've
583
00:41:57,110 --> 00:41:59,330
got here is a display with 50 pixels.
584
00:42:00,710 --> 00:42:05,670
Okay. So we're seeing something
happening here, Paul. What's going on?
585
00:42:06,500 --> 00:42:10,759
So now we're seeing the story of the
universe told by the pixel bots, and it
586
00:42:10,760 --> 00:42:14,459
started with the Big Bang, and now we've
gone to the solar system, an
587
00:42:14,460 --> 00:42:18,699
abbreviated version. Here's the sun,
here's the earth, and here's the moon.
588
00:42:18,700 --> 00:42:23,400
what we're going to see is a fish
appear, and then a dinosaur, and then a
589
00:42:23,580 --> 00:42:26,710
And that's the history of the universe
in an abbreviated form.
590
00:42:27,080 --> 00:42:29,700
History of the universe by pixel bots.
Brilliant.
591
00:42:29,900 --> 00:42:34,300
And do they, I see there's a couple of
them colliding. Do they often collide?
592
00:42:34,301 --> 00:42:38,429
Well, this is one of the things we've
worked on, is collision avoidance. So if
593
00:42:38,430 --> 00:42:41,769
you've got a swarm of robots, you want
them to go out into the world. You don't
594
00:42:41,770 --> 00:42:44,360
want them to collide with each other or
with people.
595
00:42:44,510 --> 00:42:48,689
These are little robots, and so we
forgive them if they make a few
596
00:42:48,690 --> 00:42:51,909
you will see a few collisions happen.
Yes, absolutely. So how are they
597
00:42:51,910 --> 00:42:55,670
communicating? I notice you've got some
antennas just over here as well.
598
00:42:56,010 --> 00:43:00,190
Yes, that's right. So the way this
system works is there's a camera above
599
00:43:00,310 --> 00:43:02,250
and that's connected to this computer.
600
00:43:03,120 --> 00:43:07,959
And the computer, it knows the images we
want to create. It's also computing the
601
00:43:07,960 --> 00:43:12,779
collision avoidance. And it then sends
wireless commands here, and they go to
602
00:43:12,780 --> 00:43:18,200
each individual robot. So we're saying,
robot one, go here. Robot two, go here,
603
00:43:18,201 --> 00:43:20,779
and so on. Excellent. And we're seeing a
dinosaur here.
604
00:43:20,780 --> 00:43:23,060
That's our dinosaur, yeah. Okay,
brilliant.
605
00:43:23,760 --> 00:43:24,810
Okay.
606
00:43:25,160 --> 00:43:30,680
And then, of course, evolution will give
us man at the end here. Of course.
607
00:43:31,470 --> 00:43:35,549
One step beyond these robots, and the
image will move forward. Okay, well, I
608
00:43:35,550 --> 00:43:39,649
think I'd quite like to get a volunteer,
so how about a volunteer? How about
609
00:43:39,650 --> 00:43:40,810
you, the grey jumper?
610
00:43:41,070 --> 00:43:42,120
Yeah?
611
00:43:50,050 --> 00:43:51,810
Okay, Jocelyn.
612
00:43:53,230 --> 00:43:58,529
What I want you to do is try picking up
part of the body, okay, a pixel bot, and
613
00:43:58,530 --> 00:44:00,249
pretending it's a naughty pixel bot.
614
00:44:00,250 --> 00:44:02,420
Put it over there. Just move it out of
the way.
615
00:44:10,610 --> 00:44:11,810
Okay, let's take a leg.
616
00:44:13,210 --> 00:44:14,260
See what happens.
617
00:44:18,690 --> 00:44:23,509
So you can see they're actually all
compensating for it. So now the leg has
618
00:44:23,510 --> 00:44:24,560
become the hand.
619
00:44:24,561 --> 00:44:28,129
Let's try and check it, Jocelyn. Let's
take two or three. So move a couple of
620
00:44:28,130 --> 00:44:29,180
the legs.
621
00:44:29,260 --> 00:44:31,660
And a body. Get a green one as well.
622
00:44:33,160 --> 00:44:34,780
Yeah, get a foot as well.
623
00:44:36,560 --> 00:44:39,400
Right, and then plunk them down. Let's
see how they get on.
624
00:44:42,380 --> 00:44:48,740
Wow, this is amazing, Paul. So you can
see that they want to move,
625
00:44:48,940 --> 00:44:53,099
and then not only that, they can
actually change colour. So the foot has
626
00:44:53,100 --> 00:44:55,080
become either a hand or an arm.
627
00:44:56,690 --> 00:45:01,929
and the rest of the body has compensated
for it. That's right. That's amazing. I
628
00:45:01,930 --> 00:45:04,460
don't think we can outsmart her just
then, can we?
629
00:45:04,570 --> 00:45:08,120
Unfortunately not. But that's brilliant.
Thank you very much, Jocelyn.
630
00:45:08,121 --> 00:45:09,549
The
631
00:45:09,550 --> 00:45:18,929
pixel
632
00:45:18,930 --> 00:45:22,110
bots are a little bit too small for our
keyboard players.
633
00:45:22,640 --> 00:45:27,899
So the University of Plymouth have
donated part of their robot football
634
00:45:27,900 --> 00:45:28,950
the cause.
635
00:45:29,000 --> 00:45:30,140
And here they are.
636
00:45:30,600 --> 00:45:34,720
And these little fellas have just come
back from playing football in China.
637
00:45:35,360 --> 00:45:40,140
And these six robots are able to share
information between themselves.
638
00:45:41,060 --> 00:45:45,919
So when they get an instruction to play
a note, say a key on a keyboard, the
639
00:45:45,920 --> 00:45:48,100
message is passed to all six robots.
640
00:45:48,600 --> 00:45:51,400
And the closest robot to that key will
play it.
641
00:45:52,560 --> 00:45:57,019
Now, eagle -eyed Doctor Who fans will
have noticed that they've all come
642
00:45:57,020 --> 00:46:00,440
as different incarnations of the Doctor
himself.
643
00:46:00,860 --> 00:46:03,760
I think this one's my favourite, with a
little scarf here.
644
00:46:04,020 --> 00:46:07,080
But let's hear them in action.
645
00:46:23,300 --> 00:46:24,780
That was pretty good.
646
00:46:33,400 --> 00:46:38,920
That was slightly imperfect, but not bad
for some Doctor Whos, I think.
647
00:46:39,300 --> 00:46:44,220
Now, I think that's pretty good because
our orchestra is almost complete.
648
00:46:45,440 --> 00:46:49,779
Towards the start of the lecture, I
mentioned robots will be all controlled
649
00:46:49,780 --> 00:46:51,220
using MIDI information.
650
00:46:51,930 --> 00:46:55,630
sent to each robot in real time that
would tell them what to play.
651
00:46:56,270 --> 00:47:01,589
Well, once we've gathered this many
robots, we felt the time was right to
652
00:47:01,590 --> 00:47:04,470
them all together and try it out.
653
00:47:06,970 --> 00:47:13,489
So, what we should be able to hear is
what we heard two days ago
654
00:47:13,490 --> 00:47:16,630
at the first rehearsal of our robot
orchestra.
655
00:47:17,230 --> 00:47:20,050
And here is some footage we have.
656
00:47:21,710 --> 00:47:27,470
We connected everything together and do
we want to hear it?
657
00:47:27,850 --> 00:47:31,230
Yeah. I warn you, it's not pretty.
658
00:47:31,810 --> 00:47:32,860
Here it goes.
659
00:47:52,200 --> 00:47:53,250
What do we think?
660
00:47:53,880 --> 00:47:58,219
Now, I'm not sure about you, but it
didn't quite sound like the Doctor Who
661
00:47:58,220 --> 00:48:01,590
tune I've got in my head. And it's sort
of in there somewhere, I think.
662
00:48:01,700 --> 00:48:04,980
But it wasn't great. So what was going
wrong?
663
00:48:05,640 --> 00:48:10,699
And although we were telling the robots
to play their notes at exactly the same
664
00:48:10,700 --> 00:48:17,179
time, some robots were taking slightly
longer to play their notes, while others
665
00:48:17,180 --> 00:48:19,260
were doing it very quickly.
666
00:48:20,010 --> 00:48:25,270
Now this gap is called latency, and it
makes the orchestra sound out of time.
667
00:48:26,370 --> 00:48:32,109
So we had to go around every robot and
calculate how long to the nearest
668
00:48:32,110 --> 00:48:35,990
millisecond it took each robot to play a
note.
669
00:48:36,770 --> 00:48:42,689
We then had to work out those figures
into the score, meaning we'd cue some
670
00:48:42,690 --> 00:48:47,829
robots to play a fraction of a second
before the others, so that when we hear
671
00:48:47,830 --> 00:48:50,780
the finished thing, They all sound like
they're in time.
672
00:48:52,880 --> 00:48:58,859
Now, last but definitely not least, when
designing our robot orchestra, we
673
00:48:58,860 --> 00:49:04,959
wanted to include a percussionist that
would be unashamedly cool and take to
674
00:49:04,960 --> 00:49:06,010
air.
675
00:49:06,020 --> 00:49:11,859
Now, you may have seen quadcopters for
sale in toy shops, but nothing quite
676
00:49:11,860 --> 00:49:14,280
this. Let's just watch what it can do.
677
00:49:23,560 --> 00:49:25,960
clever bit is, nobody's controlling it.
678
00:49:26,220 --> 00:49:32,159
Instead, the flight of the quadcopter is
being precisely controlled by a
679
00:49:32,160 --> 00:49:37,719
computer, and the software design has
been designed by a team at Bristol
680
00:49:37,720 --> 00:49:38,800
Robotics Laboratory.
681
00:49:39,960 --> 00:49:44,259
Now, if you look above your head, some
of you, you'll see some of these glowing
682
00:49:44,260 --> 00:49:48,900
red circles, and there's a few of them
around the lecture theatre.
683
00:49:49,300 --> 00:49:52,440
Now, in fact, these are small infrared
cameras.
684
00:49:53,070 --> 00:49:59,189
And they're looking for small balls just
like this one, which have been placed
685
00:49:59,190 --> 00:50:00,730
around the quadcopter.
686
00:50:02,610 --> 00:50:07,509
These are motion capture reflectors.
They're the same thing that filmmakers
687
00:50:07,510 --> 00:50:11,030
would use to turn an actor into a CGI
character.
688
00:50:11,850 --> 00:50:17,109
But we're using them to tell the
computer exactly where the drone is in
689
00:50:17,110 --> 00:50:18,160
lecture theatre.
690
00:50:19,400 --> 00:50:23,999
Now, on screen, you can see the position
of the cameras and the position of the
691
00:50:24,000 --> 00:50:25,050
drone.
692
00:50:25,200 --> 00:50:30,899
Now, if the drone stays in this precise
location in 3D space, those four motors
693
00:50:30,900 --> 00:50:34,980
can speed up or slow down and move it
back to where it's supposed to be.
694
00:50:36,600 --> 00:50:39,780
But it's not just a quadcopter we can
track.
695
00:50:40,440 --> 00:50:44,800
We've attached some motion capture
reflectors to this teapot.
696
00:50:45,380 --> 00:50:47,300
And if I wave this around...
697
00:50:47,880 --> 00:50:52,620
We should see the cameras are tracking
the position of this teapot as well.
698
00:50:53,660 --> 00:51:00,379
And we programmed this computer to
recognize the movement of my teapot and
699
00:51:00,380 --> 00:51:04,560
adjust the position of the quadcopter
accordingly.
700
00:51:05,000 --> 00:51:11,500
So I should be able to control this
quadcopter with my teapot.
701
00:51:12,620 --> 00:51:14,640
How good is that?
702
00:51:18,830 --> 00:51:19,880
That's fantastic.
703
00:51:23,290 --> 00:51:25,770
Now let's see how good I am at landing
this.
704
00:51:36,850 --> 00:51:38,030
Not so good.
705
00:51:45,770 --> 00:51:51,109
In our robot orchestra, the quadcopter's
tether has been connected to this arm
706
00:51:51,110 --> 00:51:56,870
down here, which is positioned so that
when the quadcopter jumps into the air,
707
00:51:57,050 --> 00:52:00,330
it will strike and crash the symbol,
like so.
708
00:52:03,070 --> 00:52:09,869
So the flight path for each of these
jumps has been pre -programmed and will
709
00:52:09,870 --> 00:52:14,770
cued by a mini -signal, just like all of
the other robots.
710
00:52:15,470 --> 00:52:17,250
So it's completely automated.
711
00:52:18,870 --> 00:52:22,950
Right. I think our orchestra is just
about complete.
712
00:52:23,350 --> 00:52:26,810
But we have a few more robot musicians
I'd like you to meet.
713
00:52:27,010 --> 00:52:29,790
So can we bring on the rest of the
robot, please?
714
00:52:39,630 --> 00:52:42,810
Now, as well as Mortimer, the drummer...
715
00:52:43,100 --> 00:52:47,879
We've also brought in this robotic drum
kit that's been designed by a team at
716
00:52:47,880 --> 00:52:49,020
King's College London.
717
00:52:49,120 --> 00:52:51,710
So can we hear a little bit from this
robot, please?
718
00:52:58,800 --> 00:53:05,040
Excellent. And at the back, next to the
quadcopter, is a pipe organ that,
719
00:53:05,180 --> 00:53:08,740
believe it or not, used to be made out
of a set of shelves.
720
00:53:09,400 --> 00:53:14,699
And it was hacked out of household items
by a researcher at the University of
721
00:53:14,700 --> 00:53:19,399
Aberystwyth. And the air is actually
being pushed through the pipes by an old
722
00:53:19,400 --> 00:53:20,500
vacuum cleaner.
723
00:53:20,800 --> 00:53:23,920
So can I hear a tune out of the pipes,
please?
724
00:53:29,880 --> 00:53:33,460
Now that's how to hack your home. Very
cool indeed.
725
00:53:34,320 --> 00:53:38,040
We've also got a robotic glockenspiel.
726
00:53:38,730 --> 00:53:45,509
And this very cool electric guitar,
which uses compressed air to push
727
00:53:45,510 --> 00:53:47,230
down the levers on the strings.
728
00:53:47,610 --> 00:53:48,830
Can we hear the guitar?
729
00:53:58,270 --> 00:53:59,650
Excellent. Okay.
730
00:53:59,930 --> 00:54:01,950
Now, as promised...
731
00:54:02,360 --> 00:54:06,999
we've invited some human musicians to
join our robot too. So please can you
732
00:54:07,000 --> 00:54:11,939
welcome Galia, Robert, Chris and Kate
from the London...
733
00:54:11,940 --> 00:54:14,039
Now,
734
00:54:14,040 --> 00:54:23,599
I
735
00:54:23,600 --> 00:54:27,800
think we're actually there. So I'll just
let you guys get comfortable there.
736
00:54:28,380 --> 00:54:33,339
And please welcome Andy Lambert from
City University London, who has been
737
00:54:33,340 --> 00:54:38,299
conducting this robot orchestra in the
past few days. A huge round of applause
738
00:54:38,300 --> 00:54:39,350
for Andy.
739
00:54:44,140 --> 00:54:48,000
I've not actually heard these robots
play together yet.
740
00:54:48,360 --> 00:54:53,979
So I genuinely have no idea how this is
going to sound. So I'm with you guys
741
00:54:53,980 --> 00:54:59,899
tonight. And even if the humans outshine
the robots, we'll have shown that
742
00:54:59,900 --> 00:55:03,700
performing in an orchestra is not beyond
the grasp of machines.
743
00:55:04,860 --> 00:55:09,419
If we can master the technologies we've
seen over the past hour, we should be
744
00:55:09,420 --> 00:55:14,739
able to make a better future for
everyone, be that 3D printing limbs or
745
00:55:14,740 --> 00:55:16,120
discovering other planets.
746
00:55:16,940 --> 00:55:20,300
I call this lecture a new revolution.
747
00:55:21,520 --> 00:55:24,480
And the hacking revolution starts right
here.
748
00:55:25,260 --> 00:55:31,339
I want you to stop thinking about your
phone or your laptop as a black box, but
749
00:55:31,340 --> 00:55:32,840
something you can tinker with.
750
00:55:33,480 --> 00:55:37,540
If your phone doesn't do what you want
it to do, write an app of your own.
751
00:55:38,640 --> 00:55:42,679
If something in your house doesn't
behave the way you want it to, think
752
00:55:42,680 --> 00:55:45,680
how you can hack it, how you can take
control.
753
00:55:47,200 --> 00:55:50,990
We set ourselves... Three grand
challenges in these lectures.
754
00:55:51,630 --> 00:55:54,310
And my final challenge is to you.
755
00:55:55,230 --> 00:55:58,090
What is your great engineering
challenge?
756
00:55:58,470 --> 00:56:00,830
What problem are you going to solve?
757
00:56:01,270 --> 00:56:04,170
And if you haven't worked it out yet,
that's okay too.
758
00:56:04,710 --> 00:56:09,769
Now is the time to get those skills,
learn some code, buy that simple
759
00:56:09,770 --> 00:56:10,820
electronics kit.
760
00:56:11,750 --> 00:56:17,810
Then, when the inspiration hits, you'll
be ready and sparks will fly.
761
00:56:19,770 --> 00:56:26,129
Now, I'm going to leave you tonight with
the first ever performance of the Royal
762
00:56:26,130 --> 00:56:28,790
Institution Robot Orchestra.
763
00:56:29,670 --> 00:56:30,870
Are we ready for this?
764
00:56:32,010 --> 00:56:35,650
Yeah? Brilliant. Okay, take it away,
Andy.
765
00:56:35,700 --> 00:56:40,250
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