BORN ROBOTS" -
Swim Like a Fish
Robots Have Feelings, Too
ALAN ALDA: Kismet here is very happy to be joining a whole
lot of other robots whose design is inspired by living things.
ALAN ALDA (Narration): Cockroaches inspire mostly loathing and
fear -- unless you're trying to build a walking machine. And
if you want a robot swimmer...
ALAN ALDA: I've taken its brain out.
ALAN ALDA (Narration): What better model than a tuna? But for robots
to be like us...
ALAN ALDA: Excuse me, I'm talking to him.
ALAN ALDA (Narration): They have to pass the slinky test...
ALAN ALDA: I'm getting it now.
ALAN ALDA (Narration): As well as play a world class game
ALAN ALDA: I'm Alan Alda. Join Kismet and me as Scientific
American Frontiers ventures out to meet a whole new generation
of Natural Born Robots.
ALAN ALDA (Narration): There was a time when people thought that
if you wanted to fly, you should do what birds do -- get yourself
a pair of wings, and flap...
ALAN ALDA: A lot of people got hurt that way. So engineers
have mostly gone their own way in making machines, using materials
and motors that substitute brute strength and raw power for
the delicate finesse that nature uses. But if engineers have
so far done just fine ignoring nature, suddenly imitating
nature has become a very desirable thing to do, certainly
among those trying to build the next generation of robots.
The reason is that when it comes to solving the really tricky
design problems, nature has a head start of three and a half
ALAN ALDA (Narration): I'm in Cleveland, at Case Western Reserve
University, about to meet some creatures that may not have
been around since life began -- but have been here way too
long for me: 300 million years, in fact, give or take a million
ALAN ALDA: Oh my God!
RITZMANN: You gotta get in close.
ALAN ALDA: Wait a minute. Oh, jeez, put it back, put the lid
on. Oh, I backed into something. They're all over the place.
RITZMANN: This is Blaberus gigantius.
ALAN ALDA: Ah!!
ALAN ALDA (Narration): Confirming my opinion of cockroaches in
general, this one immediately sets about clawing the hand
that feeds him.
ALAN ALDA: I tell you what, he and I would both feel better
if you put him back...
RITZMANN: You want to pet him?
ALAN ALDA: Do I want to pet him? No. Put him back and you'll
make us both happier. Look, you can't get rid of him.
RITZMANN: Well, they have very efficient claws, that they
engage, just like cat's claws.
ALAN ALDA: While we discuss this, could you put the lid back
on? Well, you look really happy to be in your element here.
Why are you studying cockroaches like this?
RITZMANN: Cockroaches are incredibly good locomotory animals.
They run, they jump, they turn…
ALAN ALDA: I've noticed that!
RITZMANN: And if we can get a robot to walk half as well as
a cockroach, we'll have the best robot in the world.
ALAN ALDA (Narration): Roy Ritzmann once studied cockroaches simply
out of his misplaced admiration...
RITZMANN: Roger Quinn.
ALAN ALDA: Hi Roger.
QUINN: Hello Mr. Alda.
ALAN ALDA (Narration): But for the last three years he's been working
with engineer Roger Quinn to make a giant roach robot.
QUINN: You see that it's very much like a cockroach.
ALAN ALDA: So what, do you put out a giant crumb of coffee cake
it and moves, or what?
QUINN: I wish it was that simple.
ALAN ALDA: Oh look, what's happening? If you wanted to make
something that was just like a cockroach, you succeeded. You
scared me just as much as the real cockroach did.
QUINN: Well at least it doesn't bite yet.
ALAN ALDA (Narration): Powered by compressed air, the robot
is as perfect a scaled-up imitation as Roy and Roger can devise
of a cockroach called Blaberus. Back in Roy's lab, I keep
my distance as a Blaberus is anesthetized with carbon dioxide.
ALAN ALDA: Boy, that's fast. So I take it to the extent that
he's capable of feeling anything, he's not feeling anything
Right, he's completely out.
ALAN ALDA (Narration): When it wakes up, this Blaberus, like hundreds
before it, will be going for a run on a cockroach treadmill.
Silver dots on the roach equivalent of hips, knees, and feet
will help keep track of exactly how its legs move. And wires
finer than a human hair will record from muscles in its legs
just when and how strongly they contract. With a little encouragement,
the cockroach puts on a fine display of speed. Scaled up 25
times to the size of the robot, this would be like running
at 30 miles an hour! A video camera records the run. By tracking
the white dots from frame to frame, Roy has plotted the exact
position of each leg and the exact angle of each of its joints
as it walks, runs and climbs.
RITZMANN: And so every one of the joint angles that the robot
uses to do this kind of walking and climbing has been matched
to what we got out of the cockroach. So we measured them,
they scaled it up and made the cockroach so that the joint
angles are the same.
ALAN ALDA (Narration): The robot's front legs, for example, can
move through the same range of motions as the roach's front
legs. But just knowing how the legs move isn't nearly enough.
The trickier question is how they're controlled. That's where
the wire electrodes come in, picking up the electrical signals
the cockroach gives to tell the muscles when and how much
ALAN ALDA: It changes from motion to motion, depending on
where he's going, what he's doing, it changes when he gives
RITZMANN: That's right. He's going to give a little bit more
juice here, a little bit less there, so that he'll be able
to get over things or else turn and stuff like that.
ALAN ALDA: So you really need to know that to get a robot
to be as efficient and as agile as one of these insects.
ROY RITZMANN: Exactly, exactly.
ALAN ALDA (Narration): The team especially wants the robot to be
as agile as the roach in climbing over things. So they copied
the way the cockroach uses each of its three pairs of legs
differently to get itself up and over an obstacle.
QUINN: For climbing, the front legs can come way up here and
grab on to something. But they're not so strong, so it would
be better to actually pitch the body up with the middle legs...
ALAN ALDA: And that lifts the body up?
QUINN: And then push and the whole body can pitch up like
this. Now it's in the right place for the big old rear legs
to give a mighty shove that way and drive the robot right
over the obstacle.
ALAN ALDA (Narration): The Case Western Reserve robot is far from
the first to borrow from insects the idea of having six legs.
Over the last 20 years, robots small -- and large -- have
exploited the fact that six legs enable you always to keep
three on the ground and so avoid falling over. But none of
these robots has come even close to being as agile as an insect,
because their legs don't move like an insect's. The legs of
the roach robot, its makers hope, one day will.
ALAN ALDA: What do you see this doing when it can crawl and
climb and maneuver really well?
QUINN: This is still a research vehicle. But we can see vehicles
later taking what we learn about how to do this locomotion
and for example going to Mars. An unmanned Mars mission would
be fantastic, you could climb up mountains and go places that
wheeled vehicles just can't really hope to accomplish.
ALAN ALDA: It could climb into craters here on earth too,
couldn't it, like some volcanic...
RITZMANN: Or going into jungle terrain to find land mines.
The people that put them out there are, they don't want you
to find them so they don't put them on flat surfaces and things
like that, they put them in rough terrain where wheeled vehicles
have a hard time going. Cockroaches would have no problem
and presumably this thing would not have much of a problem
if it walked like a cockroach.
ALAN ALDA: It's great, nature works all these years to make
a cockroach that we don't like, and we work to make a cockroach
that we can really use. That's wonderful.
ALAN ALDA (Narration): But while I was there, the roach robot
barely managed to lurch to its feet and look belligerent --
as if taunting Roy and Roger with the difficulty of the task
they've set for themselves. For now at least, real roaches
are preserving their 300-million-year lead.
LIKE A FISH
ALAN ALDA (Narration): Another creature robot builders admire and
envy is the tuna. Like the cockroach, it's been honed by hundreds
of millions of years of evolution to complete mastery over
its environment. And again like the cockroach, it too now
has a mechanical rival.
ALAN ALDA: Now why did you pick a tuna to study here?
TRIANTAFYLLOU: The tuna is the champion of swimmers.
ALAN ALDA: In what way? MICHAEL TRIANTAFYLLOU: In the sense
that they are very poor at capturing prey so they have to
go big distances...
ALAN ALDA: So they have to go very far. And they have to be
fast? MICHAEL TRIANTAFYLLOU: And they have to be fast so they
can cover big distances and encounter things. And they have
to swim all the time.
ALAN ALDA (Narration): This robot tuna swimming languidly down
the tow tank at MIT is helping Michael Triantafyllou and his
students understand just why tuna are such champion swimmers.
A fluorescent dye reveals its secret -- circles of water --
vortices -- flipped by its tail into its wake.
ALAN ALDA: OK, so I see these great circles come off of it.
These are the vortices?
TRIANTAFYLLOU: These are the vortices, the circles that you
see spinning, one on one side, one on the other side.
ALAN ALDA (Narration): These vortices, the MIT group discovered,
act together to propel a swimming fish through the water.
The vortices are created as water drags along the side of
the moving fish. What makes them so potent is the flapping
tail, which flips each vortex off to the opposite side. Their
spinning now combines to push a stream of water away from
the fish -- making it, in effect, jet-propelled. This insight
-- gained from studying live fish as well as the robot tuna
-- is helping design of a new generation of swimming machines.
ALAN ALDA: This is a pike you've got here?
KUMPH: Yeah, it's a robopike. Which is based on a small pike,
which is a freshwater predator, and they turn and swim and
like start really well 'cos they hide in the mud and they
come out and grab the little fish.
ALAN ALDA: This fish is more agile than other fish?
JOHN KUMPH: Yeah, it's incredibly agile. They've put accelerometers
on these things and they've measured acceleration rates that
are just absurd, like 24 Gs.
ALAN ALDA (Narration): John Kumph's robopike has an external skeleton
of plastic ribs, housing three motors that bend and flex its
body. It's controlled by a computer in its head.
KUMPH: Let's give it a try.
ALAN ALDA (Narration): The head is also the only part of the robot
that needs to be waterproof. John has experimented with several
different skins for the body -- and this one is brand new.
ALAN ALDA: Have you ever made this swim with this skin? This is
going to be the first time?
KUMPH: The very first.
ALAN ALDA: Good luck.
ALAN ALDA (Narration): After an uneasy moment...
ALAN ALDA: OK, you're getting rid of the air now?
JOHN KUMPH: Yeah, 'cos the back half is flooded.
ALAN ALDA: And this wire on here...
KUMPH: There we go.
ALAN ALDA: Oh look, it's right side up. This wire just supplies
power, you're not controlling the fish's movement with this,
KUMPH: Exactly. I think that's working. Let's give this a
try and see if it's still swimming.
ALAN ALDA (Narration): One thing I'm learning about robot researchers
is that their creations are never actually finished.
ALAN ALDA: Ah, here, it's wiggling.
KUMPH: Ah, it's wiggling, uh?
ALAN ALDA (Narration): Their robots are always being taken apart,
tweaked here and there, then they're put back together to
see if they're improved. What all this means is that visitors
like me often turn up at just the wrong moment...
JOHN KUMPH: I'm a bit worried there's a leak in the nose cone.
See those big air bubbles coming from there? I'm going to
take it out in a second. See how heavy it is?
ALAN ALDA (Narration): So a sinking robot pike joins the stubborn
robot roach in demonstrating just how hard it is to copy Mother
Nature. Though in this case the problem's straightforward
-- a leaky head gasket.
KUMPH: There's the water coming out of the computer.
ALAN ALDA (Narration): A brain drain and a slow bake in a low temperature
oven are all it takes for the robopike to swim again. But
it's clear that it will need many more upgrades before it
can compete with its role model. Meanwhile, another mechanical
fish has already made it out of its hatchery. This robot tuna
was built by a team headed by Jamie Anderson.
ALAN ALDA: Ah, you got the tail off, huh? That's what it looks
ANDERSON: That's what's powering the fish. Four hydraulic
cylinders, one activating each link.
ALAN ALDA: So what, it bends right there?
ANDERSON: Yeah, you can see the four pivots. There's one here,
we call it the hip, the most powerful joint. And there's one
right here. It's kind of stiff right now 'cos it's full of
hydraulic fluid. There's one here. And then this one on the
ALAN ALDA: Right on the very end.
ANDERSON: ...where the caudal fin hooks on.
ALAN ALDA: These flippers down here don't look biological
ANDERSON: No, those are conventional engineering style control
surfaces. This is the same type of surface you'd have on an
underwater vehicle like a submarine or torpedo. We designed
these to break away so if the fish actually hit a wall or
a rock or something it would not damage the pressure hull.
ALAN ALDA: What are they doing here?
ANDERSON: Right now we're pulling on the neoprene skin. You
see this joint ring here will engage the back of the pressure
hull. That is screwed on in a number of places. And then we
secure this flap of skin down so it has a very smooth hydrodynamic
ALAN ALDA (Narration): The robotuna is about to go swimming in
the test tank of the University of New Hampshire. But it was
built by Jamie and her colleagues at the Draper Lab in Cambridge
ALAN ALDA: What's this cable here?
That's an umbilical that enables us to update the program
that runs inside the fish, tell sit what to do and where to
ALAN ALDA: So you're sending data from the computer through
Correct. We're downloading a mission script that tells the
fish where to swim and how fast to swim.
ALAN ALDA: Is it okay if I unplug this now?
ALAN ALDA: What do I do?
Pull straight up.
ALAN ALDA: Straight up.
There you go.
ALAN ALDA: Taken its brain out.
ALAN ALDA (Narration): Apart from its brain, the robotuna is self-sufficient.
The pressure hull that's the front two-thirds of its body
houses batteries and motors to activate the hydraulic links
that flap its tail. Its speed right now is limited to one
body length per second -- about half that of a cruising tuna,
and only a fraction of the speed of a tuna going flat out.
But swimming with it, it's hard to believe it isn't alive.
ALAN ALDA: You know, when I swam with seals in the Galapagos,
it was a little different because they played with me. But
this guy swam as if he had a mind of his own and he was just
in the water, swimming. I mean it was like that's what he
That's what he does.
ALAN ALDA: And if you change what's in his brain, he does
ALAN ALDA: What are you going to put in his brain now?
We'll have him swim straight down to the length of the pool
and then take a hard right at the end.
ALAN ALDA: OK, you want to put the cable in?
ALAN ALDA: I think I knocked off his flipper again.
We'll fix that.
ALAN ALDA (Narration): What makes a robot fish attractive as an
unmanned underwater vehicle is that in principle it is much
more efficient than a conventional submarine. The invisible
vortices streaming of its tail push it along without all the
wasteful churning of a propeller. And it can turn on a dime.
ANDERSON: What the tuna will do for you is it will give you
increased maneuverability, you'll be able to go into places
you wouldn't normally fit -- say you want to swim up a pipe,
to check the sewage out-fall, or go into waves, into a harbor.
This enables you to go potentially further, faster and be
more maneuverable when you get there.
ALAN ALDA: If you want I suppose one day you could make a
tuna that would hook up with a school of tuna and find out
how they operate all around the world.
ANDERSON: That is a wonderful mission. As a matter of fact,
there is very little known about tunas. Because they swim
for a living, it's hard to keep up with them, so scientists
would love to have an imposter in the school to keep track
of their movements.
ALAN ALDA: We've got to come back and do a story about that...
ANDERSON: I hope we get to that point.
ALAN ALDA: It would be really fun to see how they accept it.
Maybe they'd kind of like it, you know, a special tuna --
"Look, he's already in the can!"
ALAN ALDA (Narration): Robots, to most people, mean machines based
not on insects or fish, but us. The robot recently unveiled
by Honda certainly qualifies. Modeled on how people move,
it wowed the world of robotics with its superb engineering.
But right now it's an elaborate puppet, its every motion controlled
by an operator behind the scenes, or programmed in advance.
Change the width of these stairs, for instance, and the robot
would be in trouble. To really walk as a human walks means
you have to really understand how people do it -- and that's
the reason for this machine, strutting its stuff around a
basement laboratory at MIT.
ALAN ALDA: Is it helped to stand erect in any way by this bar?
PRATT: The boom keeps it so it can't go side to side. It only
ALAN ALDA: Uh, it seems to have taken a dive.
ALAN ALDA: What happened?
PRATT: One of the motors gave out. I'm having a problem with
one motor, I have to fix it...
ALAN ALDA (Narration): I'm beginning to wonder if I'm some sort
of robot jinx, but happily Jerry Pratt is unfazed.
PRATT: It's usually pretty reliable. Probably walked about
ten miles since I built it.
ALAN ALDA: You're imitating a human gait, but you don't have human
materials here, you don't have any muscle or...
PRATT: The materials we have to work with are a lot different
than biological materials, but we still can get a lot of the
flavors of controlling the motion.
ALAN ALDA (Narration): The robot gets a natural spring to its step
not from muscles and tendons but from actual springs built
in to its motors.
ALAN ALDA: Do you keep having to go back to studying legs and feet
and stuff every time you run into a problem to see how nature
JERRY PRATT: Yeah, we watch a lot of video, watch a lot of
people walking on treadmills and animals. And it's just, almost
frustrating how good they are at walking.
ALAN ALDA: But you've been watching people walking for all the
years of your life.
PRATT: Well, I've been walking for all but two years of my
life, and I don't know how I do it.
ALAN ALDA (Narration): For instance, there's the little matter
PRATT: One nice thing that we found by looking at nature is
kneecaps. What are they good for? One way to look at it is,
if you don't have a kneecap, your leg is in a kind of buckling
configuration. It wants to buckle in one direction or the
other, and to control that is rather difficult, because if
it's a little bit that way, you've got to push it that way.
If it's a little bit that way, you push it that way, and it
will start chattering, what we call chattering. If you have
a kneecap, you can simply push it until you hit the kneecap,
and that's it.
ALAN ALDA (Narration): But Jerry Pratt has a bigger goal than simply
making a robot walk like a person.
PRATT: Say you have a person who has a spinal cord injury,
and they can't control their legs anymore. If you have to
control their legs for them, you have to know what...
ALAN ALDA: You have to do it in a way that would work best...
PRATT: So the more you understand what walking is all about,
the more you can build these devices.
ALAN ALDA: That's very interesting. I hear that over and over again,
that as we look at nature and make machines that copy nature,
we understand nature better. It's funny, because you'd think
you'd have to understand it an awful lot to be able to make
the machine, and yet making the machine actually gives you
a deeper look at nature, doesn't it?
PRATT: Yup, it's a two-way street.
ALAN ALDA (Narration): Banging its own drum is a robot that's being
built specifically to explore that two-way street between
nature and machines.
BROOKS: Alan, if you get hold of this, you'll be able to feel...
ALAN ALDA (Narration): We first visited Rodney Brooks and his creation
COG at MIT six years ago. Back then Rod was unusual in taking
a biological approach to robot design -- and widely regarded
as arrogantly ambitious in choosing to model not an insect
or a fish, but a human being.
BROOKS: By being a human shape and having the same arrangement
of eyes, etc., it will encourage people to interact with it
as though it was human, and it will have the same sort of
experiences that a human has when a human develops.
ALAN ALDA: Last time I was here... ha, excuse me, I'm talking to
him... last time I was here, he could do some basic things.
I was wondering, what can he do now that's different?
SCASSELLATI: We do a lot of different things right now. Partly
we've built on the skills that we acquired earlier, but what
we've also moved into is some more manipulative tasks, doing
things with the two arms that we have now, and also some more
social tasks, of more interaction with people.
ALAN ALDA: What's it interested in doing? I mean, here it's looking
at my hands. What is it planning to do about that?
SCASSELLATI: Well, right now it doesn't plan to do much other
that pay attention to what's happening. So the robot attends
to certain things like movement, faces, quickly moving objects,
brightly colored objects.
ALAN ALDA: That tilt of the head and the eyes really focusing in
does give you the impression that it's paying attention to
ALAN ALDA (Narration): In 1994, COG had only one arm -- and that
was still attached to the laboratory bench. Two years later,
arm in place, COG was learning to reach. This time, COG has
both his arms -- and has, apparently, become a very bad drummer.
Now I confess to being baffled as to what Matt Williamson
is trying to prove here. I think the idea is for COG to pick
up Matt's rhythm, but the opposite seems to be happening.
ALAN ALDA: Yeah, it sounds to me like you're starting one rhythm
and then you're synchronizing with its rhythm, and it's not
changing its rhythm. It's a lot smarter than we are, I see
what you mean!
ALAN ALDA (Narration): So I have a try. What's supposed to be happening
is that COG should be synchronizing the drumbeats by listening
to both my beats and its own. But I don't hear it. What's
more, I don't quite get the point.
ALAN ALDA: Can you tell me what you're doing here that's different
from other robots?
MATT WILLIAMSON: The difference is having the feedback loop
that appears on the surface to be completely irrelevant!
ALAN ALDA: What is it at a much deeper level?
ALAN ALDA (Narration): Matt, a very patient young man, sets up
COG so that its left hand doesn't know what its right hand's
doing, except by listening to it.
ALAN ALDA: Make it not listen, OK? OK, sometimes it's in phase
and sometimes it's not.
ALAN ALDA (Narration): Matt now switches on COG's ears.
WILLIAMSON: It's listening now.
ALAN ALDA: Yeah, it took about three or four beats to find itself.
MATT WILLIAMSON: Yeah, that's 'cos it's listening to both
ALAN ALDA (Narration): I think I'm getting it. The trick is to
stop thinking of COG as a conventional robot. If it were,
you'd simply program the two arms to hit together. But then
you'd miss the fact that the right drumstick is free to bounce,
and so it isn't completely predictable.
WILLIAMSON: Exactly. That is exactly the point.
ALAN ALDA: OK, now I get it. OK, this is good. You see, you couldn't
get a machine to understand this way.
ALAN ALDA (Narration): Matt promises that COG's next party trick
will demonstrate the point more obviously.
MATT WILLIAMSON: We've got the two arms and they're moving
completely independently. Each joint is moving up and down
ALAN ALDA: Yeah, I don't see any particular pattern in the way
WILLIAMSON: What we can do is we can, if we connect the two
arms through the slinky, they are now coupled through this
mechanical coupling of the slinky itself, right?
ALAN ALDA: Now, they're really doing it the way a little kid would
to make them go back and forth. And it found that rhythm pretty
quickly, in just a couple of gestures, a couple of cycles.
WILLIAMSON: So what's happening is that as the weight of the
slinky goes from arm to arm, the control of the joint is sensing
that weight and adjusting how it moves to produce this motion.
ALAN ALDA: So the signal that it's looking for is the full weight
of the slinky. It knows it's going to work with a slinky,
ALAN ALDA: Or does it?
WILLIAMSON: I don't like saying it knows it's working with
ALAN ALDA: Right, fine, it's not a person to that extent yet, but
its looking for a signal that is the weight of the slinky.
When it gets that signal, it's programmed to toss it back
the other way.
WILLIAMSON: Exactly, exactly. The only motion the two arms
are kind of happy in is ones where they're moving in this
sort of out of phase motion.
ALAN ALDA: Kind of happy, huh? You're talking as if it's alive.
WILLIAMSON: Well... I know.
ALAN ALDA: It's hard not to.
ALAN ALDA (Narration): Now, just when COG is kind of happy with
its pink plastic slinky, Matt switches it for a heavier metal
WILLIAMSON: There we go.
ALAN ALDA: It found it. It found it in, like, two tries. And look,
the rhythm is completely different now. It's vroom, vroom...
vroom, vroom. It's a very different rhythm. And it's not programmed
-- I'm getting it now -- it's not programmed to have a certain
rhythm depending on what weight you put on, it finds the weight
of the slinky because it just responds to whatever you do
ALAN ALDA: It's responding to the world outside and adjusting itself
to that world. That's really interesting. That really is more
like the way people work than the way a lot of robots work.
WILLIAMSON: I think so. I hope so.
ALAN ALDA (Narration): But for COG's creator, there's at least
one major skill people have that COG still doesn't.
BROOKS: I wish we had the system being able to understand
objects better than it can. It doesn't understand objects.
ALAN ALDA: Meaning what?
BROOKS: It's sitting in a sea of movement, and faces it understands
but it doesn't understand that this is a slinky and that this
is a slinky, and they look different but they're really the
same sort of thing. It can tell that when you attach them
but it can't look at them and figure that out for itself.
ALAN ALDA: What would that enable you to do when you get that hurdle
BROOKS: That will enable COG to generalize from previous acts
and future acts. And that generalization is a key to the further
development of a child.
ALAN ALDA (Narration): Since COG was born, its major inspiration
has been the way a child explores its world. But children
have to master social as well as physical skills. Can robots
learn to be social? Stay tuned.
HAVE FEELINGS, TOO
ALAN ALDA (Narration): Roving among fossil dinosaurs in Pittsburgh
is a robot that may not look very human, but is programmed
to act like one.
ALAN ALDA: OK, here you go.
Hello, and welcome to Dinosaur Hall at the Carnegie Museum
of Natural History. I'm SAGE, the world's first Self Aware
Guided Electro-educator -- sort of like Socrates, Aristotle,
Galileo and Einstein all rolled into one. With wheels! But
you didn't come here to learn about me, did you? You came
here to find out about dinosaurs.
ALAN ALDA: I actually came here to learn about you.
ALAN ALDA (Narration):
is a robot with attitude. Stand in its way too many times,
and it can get a little testy.
Excuse me. I'm giving a tour right now.
NOURBAKHSH: It has a lot of different emotions. So it has
frustration, loneliness, confusion, happiness; and you can
think of each of these as a little bar, a little meter, that
goes up and down. And gradually over the course of the day,
depending on how people interact with it, each of these will
go up and down slowly.
ALAN ALDA: You mean if it gets too many bad interactions earlier
in the day, it's crankier at the end of the day than it was
at the beginning of the day?
NOURBAKHSH: Yeah. Now, it wears off...
ALAN ALDA: Why? What's the advantage of having a robot? I can hire
people to do that…
NOURBAKHSH: Just like a human being...
ALAN ALDA: That's what I get most of the time when I go into a
store on a bad day!
NOURBAKHSH: Exactly. And the reason we want the robot to act
that way is because people respect it more. So if a robot
acts like a machine, you keep playing with it, you get in
front of it and you don't care if it doesn't go right, you
just stand there and say, "I'm smarter than you, ha, ha, ha."
But when it actually responds and emotes, then people actually
pay attention. And they go, "Oh, excuse me, you're giving
a tour, I'm sorry." So the reason we take inspiration from
the way humans behave emotionally is because it makes it do
a better job of interacting with humans.
ALAN ALDA (Narration): Just the fact thatSAGE
moves and talks already makes it a magnet for children.
ALAN ALDA: The kids love following it, don't they?
ILLAH NOURBAKHSH: Yeah, they attribute life to it because
I'm going to wait till you move. I'm a robot. I'm more patient
ALAN ALDA: He's so happy to be able to stop the robot.
ALAN ALDA (Narration): At the end of each day's work as a tour
guide, SAGE e-mails Illah with an account of how things went.
ILLAH NOURBAKHSH: It says, "I gave 15 tours today, Illah,
and my happiness level is at 95%, my frustration's at 5%,
and I'm a little lonely."
ALAN ALDA: A little lonely! How do you use that information?
NOURBAKHSH: We play with the way it behaves with people. So
we actually play with its affection, the way it interacts
with people. We'll change how frustrated it makes itself sound.
We'll change how noisy it is when it's lonely.
ALAN ALDA: Then you check to see if further interaction with people
makes a happier machine.
ILLAH NOURBAKHSH: Exactly.
ALAN ALDA: And do you want a happier machine?
NOURBAKHSH: We love happy machines. Because the way it gets
happy is with good interactions with humans.
ALAN ALDA: (Narration) Illah foresees robots you can relate to
not just in museums, but throughout society. And he's not
ALAN ALDA: You know, when you first walked in, I thought you
were holding a real baby. There was something about the way
you were holding it.
ALAN ALDA (Narration): Helen Greiner's baby is actually a robot
GREINER: Like a baby, if you don't treat it well, it will
start to get cranky. But if you play with it, and if you nurture
it, it will remain happy and responsive and gurgle and coo
and act like a real kid.
ALAN ALDA: Oh, it's unhappy.
ALAN ALDA (Narration): Bit's slightly spooky realism is another
attempt to make robots less like machines and more like us.
GREINER: The idea is that as robots become more ubiquitous,
they need to act more and more like things we think of as
alive, so we know how to interact with them automatically
basically. If you give this to someone, they'll start treating
it like a real baby.
ALAN ALDA (Narration): Well, we'll see.... Bit Burp.
GREINER: You got it to do one thing!
ALAN ALDA: It's really into belching.
HELEN GREINER: How about giving it its bottle?
ALAN ALDA: Alright, here.
ALAN ALDA (Narration): It's a strange feeling. Bit's very
obviously not real, but it's hard not to empathize with it.
ALAN ALDA: Heh, heh, heh, there's a definite smile there. That's
great, I mean it's... quiet… it's amazing how you get such
a range of expressions.
GREINER: They key is to have a behavioral control system that
has a lot of really small simple rules all running in parallel
that builds complexity from the ground up.
ALAN ALDA: Oh, look at that distress. Maybe it just has gas. What's
GREINER: Well, although it looks like a baby on the outside...
ALAN ALDA: Oh. I saw this movie.
HELEN GREINER: What it really is, is a mechanism and a computer
and sensors over its body...
ALAN ALDA (Narration): Bit was created by a company called IS Robotics,
and is the direct descendent of a robot I met six years ago.
ALAN ALDA: It, wake up. Oh, very good. Hello, good morning.
ALAN ALDA (Narration): "It" was also created at IS Robotics...
ALAN ALDA: I'm sorry. Could you just say that again.
ALAN ALDA (Narration): The company had been recently founded by
Rodney Brooks. "It" was able to react to things like getting
too close to its infrared detectors with a caricatured human
ALAN ALDA: Heh, heh, it opens its mouth in utter surprise.
BROOKS: Yeah, and it raises its eyebrows. It's got this reaction
of, "Oh, what's happening here, get away from me."
ALAN ALDA (Narration): "It" was one of the first attempts to give
robots an appealing if somewhat exaggerated appearance of
RODNEY BROOKS: It tries to appear to be human, so that we
can interact with it in a way that's human.
ALAN ALDA (Narration): This idea has now found its fullest expression
in a robot called Kismet, being brought to synthetic life
in the same MIT lab that COG inhabits.
ALAN ALDA: These robots, like babies, are going to seem especially
appealing to us. We spend a lot of time with babies, and we
can't resist them.
ALAN ALDA (Narration): Kismet's expressions -- ranging from boredom...
to happiness... to sadness... to interested... -- are deliberately
BREZEAL: It's very much a caricature to make it that much
easier for you to read the robot. So that when it looks happy,
it's obviously happy; when it looks sad, it's obviously sad.
You kind of go, "Oh, I did something to upset it. I should
do something to make it happy." So it's really trying to get
you involved at this kind of unconscious emotional level.
ALAN ALDA (Narration): Cynthia spends long hours in front of Kismet,
as she works on giving it giving the ability to recognize
objects and react with its cartoon-like response. And her
willingness to invest the effort is itself a demonstration
of the goal of the research -- to make people want to help
their robots, so that robots can more easily learn the ways
of humans. The idea is that one day, COG himself will have
a Kismet-inspired head, so that its human companions will
treat him like an endearing -- if somewhat clunky --child.
Right now, Kismet can make facial expressions but can't recognize
them. That's Cynthia's next task -- but it's one she believes
Kismet itself will help with.
ALAN ALDA: Facial expressions are so subtle. How can you tell
whether I'm smiling or making an angry look?
CYNTHIA BREZEAL: This is the nice thing. When parents interact
with young children -- that's another reason this is a robot
infant -- we have very exaggerated behavior. We're leveraging
off of that. If you're dealing with an adult, you know...
I might smile a little, I might shift my gaze and so on...
but it's very subtle cues. When you're playing with an infant,
you're very exaggerated. Your face is exaggerated, your intonation...
"Oh, you're such a good robot"... you know, everything is
ALAN ALDA: You're such a good robot!
CYNTHIA BREZEAL: Exactly... that it's making the perceptual
problems for the technology much easier than it would be if
you were trying to interact at a human level.
ALAN ALDA: So you're counting on that behavior?
BREZEAL: I'm very much counting... I'm trying to pull it from
ALAN ALDA: Yeah, yeah, I see.
ALAN ALDA (Narration): But one thing's been nagging at me all during
our encounters with robots that their makers describe as happy,
or frustrated or surprised. What's really going on in these
machines is that little computer programs are running that
enable each robot to appear as if it's feeling.
ALAN ALDA: I mean, if it makes faces and changes expressions, we'll
read stuff into that. But how can it possibly have a base
from which to be surprised, for instance?
BROOKS: Right, this is the really big question, I think. Whether
we can make machines really, really, really be surprised,
really, really understand, or just appear to be surprised.
That's I think the...
ALAN ALDA: How can they possibly feel? I mean what would represent
BROOKS: Well, in principle, I think we're machines. You know,
we're made up of lots of mindless little atoms and molecules
which work together, and they produce this behavior. Now,
some vitalist might say that there's an elixir of life inside
us, or some people might say there's a soul, but as a scientist,
fundamentally, I think we are just... I think we are just
machines. Now, I don't treat you like a machine...
ALAN ALDA: Not so far, anyway.
BROOKS: I'm willing to treat COG as... COG doesn't have it,
but you have it.
ALAN ALDA: That gets right to the point of it. You can take COG
apart and put him back together again. You can't do that to
me -- take me all apart...
BROOKS: Surgeons can do a lot...
ALAN ALDA: Yeah, but take me all apart; you take all the little
parts you talked about and try to put them back together,
there's going to be something missing.
BROOKS: Well, that's how we think right now. But suppose we
get these robots to the point where they really make me feel
as comfortable with them as you make me feel comfortable --
have all these social cues, have all these social interactions
-- and then at the same time, I'm able to take them apart
and put them back together. What does that say about us?
ALAN ALDA: Let's say you can do that. Let's say you can get a machine
to give every indication that it's feeling stuff. So what?
What will that do? Will that just make me more comfortable
with my computer, or what will that do? How will that change
BROOKS: I'm interested in understanding what it is about us
that makes us human, what aspects. I'm trying to do the reduction,
which science always tries to do, the reduction. Science looks
at chemical processes and tries to break it down to the simplest
things. This is my attempt at trying to break down what it
is that makes us human into simpler components to therefore
MATARIC: Think of yourself as the mother duck. Now you're
the mother duck.
ALAN ALDA: Haven't played that part before.
ALAN ALDA (Narration): What's more, I suspect the robot ducklings
ALAN ALDA: It's crawling up my leg! I hope you can explain it...
WERGER: There's a very large gap between these two sonars,
and when an object is at precisely this angle, the robot has
a lot of trouble sensing it.
ALAN ALDA: Look at this. They keep standing on my foot. What is
he doing? What does he want from me?
WERGER: They want you to move.
ALAN ALDA (Narration): At the University of Southern California
in Los Angeles, Maja Mataric and Barry Werger are trying to
get robots to behave like animals that live in social groups
-- ducklings, for example... My status as mother duck is conferred
by the orange tube taped around my leg.
ALAN ALDA: He's still sensing me, isn't he? What is it, the
little camera on top?
MAJA MATARIC: Yeah. The camera sees your leg, it sees the
orange, and it says, "Mommy, I'm lost in the grass!"
ALAN ALDA (Narration): While the camera is looking for me, the
sonar on each robot is checking for obstacles. What's amazing
is that while the programs Barry has written for the robots'
computers are very, very simple, the robots' behavior is anything
ALAN ALDA: Oh look, he went around that tree and found me
again. This is really good. Is he tuned in primarily to the
camera so he's trying to find...
BARRY WERGER: The trick is the part of the robot, the consciousness
that's trying to find your leg is completely independent from
the part that's trying to avoid the obstacles. And they actually
kind of battle it out inside the robot's brain to decide who's
going to take control of the robot. So the priority always
goes to the obstacle, because that's the danger. When something's
in its way it always does what it takes to not hit something.
And then, if it's not actively avoiding something then it
goes towards the object of desire.
MATARIC: You might ask, why do we do it this way? Why don't
we just put one big program the way people traditionally do
or traditionally used to do in robotics. And the whole point
is that we're being biologically motivated. So in biology,
we know that the brain is distributed and there are collections
of drives, some very, very old drives like run away from anything
that's attacking you, or go follow the mother. And that's
exactly the drives we're modeling here.
ALAN ALDA (Narration): Many living things act collectively, cooperating
to achieve tasks like getting food. In this experiment, Maja
and her students study different ways a group of robots can
collaborate to gather up hockey pucks as efficiently as possible.
MATARIC: That's the queen bee. She takes care of the home
region and they take care of the rest of the world. And see,
they're doing a good job. There's almost nothing left.
ALAN ALDA (Narration): Again, like the robot ducklings, these mechanical
bees are following very simple rules. Among humans, soccer
is a game in which simple rules -- and brilliant technical
skills -- can combine to produce dazzling complexity -- as
if the team shares one big mind. A few years ago, a small
group of robot researchers began arguing that getting robots
to play soccer would be what Maja likes to call "the grand
MAJA MATARIC: And it was not at all widely accepted. People
said, "Oh this is just fun and games, what's soccer? Big deal,
you just move around and kick the ball." Turns out, it's really,
really hard. And it's hard for two reasons. Because at the
low level you have to find the ball, kick the ball -- you
know, survive. At a very, very fast clip. That's very hard.
So robotics cannot do that yet. And then at another level,
you have to have strategy. You have to interact with your
team, figure out who should do what so that you win.
ALAN ALDA (Narration): Speed and strategy -- those are the keys
to success in robot soccer. And few groups have done more
to achieve them than the research team at Carnegie Mellon
University in Pittsburgh, headed by another of the originators
of robot soccer, Manuela Veloso.
VELOSO: Shoot again, shoot!
ALAN ALDA (Narration): One of the stars of CMUnited is their goalie.
Trying to beat it gives me the chance to learn some of the
secrets of the team's success.
ALAN ALDA: How is this working? Does that little guy have eyes
in its head somehow?
MANUELA VELOSO: No, actually the robot does not have any eyes.
There is a camera that is overhead and sees the whole field.
ALAN ALDA (Narration): From the video image, a computer extracts
the position of the ball and any robots on the field. Then
it predicts from the movement of the ball its current direction
and speed -- indicated by the length of the line. The computer
does this 30 times a second -- fast enough to cope with all
but the speediest shots.
VELOSO: There you go.
ALAN ALDA: I went too fast.
STONE: Vision's fine.
ALAN ALDA (Narration): Behind the scenes, Peter Stone's running
the vision system, while Mike Bowling's laptop is sending
wireless instructions to the robots on the field. But during
competition, it's hands off.
ALAN ALDA: You're not allowed, by the terms of the competition,
to give it any directions from a human during the game?
MANUELA VELOSO: Yes, we cannot give it any directions.
ALAN ALDA: It all has to be done beforehand, as you design the
VELOSO: Right. And the challenge is that the domain, the task,
is very uncertain. So we have to up front program or make
the robots think about a very large number of situations.
ALAN ALDA (Narration): One of the things the robots think about
is when and where to pass.
VELOSO: Now, here is a pass.
ALAN ALDA: Oh yeah, yeah. That was a real pass.
MANUELA VELOSO: It's actually trying to predict where the
ball is going to be. So it needs to think about where is the
best point where it should intercept the ball.
ALAN ALDA: Does that help you to actually think of them as thinking
and being confused? Is that a real description of what's happening,
do you think?
VELOSO: We want to build robots, but we are humans, right?
So we can only build them similar to how we think ourselves.
So that's why formations came about, roles came about, your
strategy comes about by thinking, how would you do?
ALAN ALDA (Narration): For instance, if you're a defender faced
with two attackers, when and how would you clear the ball?
The CMU defender is programmed to check the gap between the
attackers to make sure it's wide enough before kicking the
ball between them. If the attackers are too close, the defender
clears the ball to the side. With four months to go before
the robot soccer contest, the CMUnited team is in good spirits.
MANUELA VELOSO: Shoot, shoot!
ALAN ALDA (Narration): Even during practice scrimmages, Manuela
finds it hard to contain her competitive instincts.
ALAN ALDA: Now look, you designed this. How can you be talking
to it as if it can understand you? Shoot, shoot, go, go!?
VELOSO: I know!
ALAN ALDA (Narration): CMUnited's speed and strategy have already
won past robot soccer championships. But in this year's contest,
to be held in Stockholm, they'll be up against some formidable
ALAN ALDA: What do you think? Do you think you'll win in Stockholm
VELOSO: Let me tell you. Probably we will. I'm not sure. But
if I ask Mike and Sorin and Huan and Peter...
ACHIM: We win.
MANUELA VELOSO: Sorin says, "We win."
SORIN ACHIM: I always think we are going to win. We did it
ALAN ALDA: You always do, right?
ALAN ALDA (Narration): Stockholm in August. Outside, the temperature
is in the 80s.
Three, two, one...
ALAN ALDA (Narration): Inside, it's even hotter, as teams from
around the world compete before an audience of computer scientists
in RoboCup 99. It's the quarter-finals, a match between a
team from Singapore and one from Cornell University -- and
Cornell strikes first.
D'ANDREA: Oh, yeah!
Three, two, one...
ALAN ALDA (Narration): Along with CMUnited, Cornell's team, Big
Red, is a favorite to win. Fast and strong, its robots can
play different roles at different times.
D'ANDREA: This is a very good role for us. It's called "corner
shoot". If we have the ball in the corner and we notice that
the goalie is slightly out in the field, we just do a quick
spin with the hope of putting it across the crease hoping
that either one of our players rushes in or that it accidentally
goes off their player, which is exactly what happened.
Three, two, one...
RAFFAELLO D'ANDREA: It's all based on the position of the
players and the position of the ball. We have another role
called "jam and shoot". If it sees the ball and there is no
opponent nearby and there's a clear line to the net, it just
rushes it and goes for the net.
ALAN ALDA (Narration): Sorin Achim from CMU watches anxiously
as Singapore's only goal comes from a penalty, and Cornell
sweeps on to a convincing win. Also witnessing the victory,
both as competitor and mentor, is CMU's Manuela Veloso.
RAFFAELLO D'ANDREA: We in fact invited Professor Veloso to
give a talk at Cornell, because they are right at the forefront
of AI research, and we wanted Professor Veloso to tell us
what strategies they took, and we based a lot of our artificial
intelligence on what they've done. So we definitely borrowed
from our competitors.
ACHIM: I lost my confidence. I guess if we get to the final
and play against Cornell we need a lot of luck to win.
ALAN ALDA (Narration): In fact, CMUnited's luck is to run out well
before the final. After easy wins in the qualifying rounds,
CMU's robots in their quarter-final match seem hesitant and
confused. Manuela Veloso: Clear. Clear. Clear now!
ALAN ALDA (Narration): Against the fast and aggressive robots of
another team from Singapore, Lucky Star, the CMU team is getting
literally pushed around.
Charging. Yellow card for robot number three. And it's a free
kick for CMU.
ALAN ALDA (Narration): This play sums up the match. A penalty attempt
by CMU turns into a beautiful goal for Lucky Star... who go
on to crush CMUnited 8-0.
VELOSO: We are sad. But it's somehow... we did not change
any of our hardware, so it's the same robots as '98. Technology
improves every year. They came with much faster robots than
ours, and definitely we were still always worried about strategy
and not making the robots faster. So... they just won!
ALAN ALDA (Narration): Now it's Big Red's turn to face Lucky Star
in the first semi-final.
RAFFAELLO D'ANDREA: This is the fastest team that we've played
against, so we have to be sure we can cope with their speed.
ALAN ALDA (Narration): And it's immediately obvious that this is
going to be a match between two superbly skilled teams. Cornell
strikes first -- and more often. Big Red's robots more than
hold their own in both speed and strategy to win the first
D'ANDREA: Excellent game, guys.
ALAN ALDA (Narration): In the other semi-final, a team of just
three amazingly speedy and maneuverable robots from Korea
faces the stolid but powerful machines of the FooFighters,
from the Free University of Berlin. The FooFighters' weapon
is a devastating kick... delivered by rotating paddles at
the front of each robot. Their shooting skills win the game...
and cause the Cornell team to make some last-minute adjustments
before the final.
D'ANDREA: What we've done is we've always made sure that we
position our midfielder always between the ball and the goal
at a slight offset and the goalie will take up the rest.
ALAN ALDA (Narration): The plan succeeds brilliantly.
Three, two, one...
ALAN ALDA (Narration): Big Red's defense is more than enough to
stop the powerful shots of the FooFighters -- and Cornell's
attacking game is relentless. Final score: 15-0.
VELOSO: And the first prize is for Big Red from Cornell University,
who only suffered two goals during the whole tournament.
ALAN ALDA (Narration): Cornell's win was in one of no less than
four different robot categories at RoboCup 99. In a sign of
things to come, one of the other categories was for teams
of four-legged robots. The robot dogs are very obviously beginners.
But like all the other robots in the contests, they're on
their own once play begins. All their programmers can do is
cheer them on.
VELOSO: Go blue!
ALAN ALDA (Narration): But for Manuela Veloso and her colleagues
in robotics research, the challenge of creating robot teams
goes far beyond the soccer field. Their goal is teams of autonomous
robots cooperating on complex tasks like search and rescue
missions, or building space stations -- even cleaning house.
Meanwhile, the RoboCup organizers have their own dream: a
team of humanoid robots taking the field against the winners
of the Soccer World Cup in the year 2050.