[MUSIC PLAYING]
Thanks.
I'm delighted to see this experiment working.
So I'm going to tell you a little bit about what
this is about, and then Ara will tell you the details.
The program I direct, CBA, is a cross campus activity
at MIT for people like me, who never understood
the difference between computer science and physical science.
Who work right at the boundary of hardware and software,
where you can't tell them apart.
CBA was started with an ambitious NSF
proposal, where we said we wanted one of every tool,
of every size.
And we got NSF on a good day, and they said yes.
So we run a facility that, from atoms up to buildings,
we can make almost anything, for the research.
And then around that are many different disciplines working
right at that interface.
So physicists, chemists, biologists,
lots of different disciplines of people
anchored in the discipline, but with sort
of a foot that doesn't fit in the discipline
at this boundary.
So molecular quantum computers on up.
And one of the broad themes that's
emerged from the research is the idea of digital fabrication.
And what it doesn't mean is a computer controlling a machine.
In 1952, MIT connected the first computer to a milling machine
to make something.
And since then, there's a lot of attention
to things like 3D printers.
But the real revolution coming in the research
isn't a computer controlling a machine.
That happened in the 50s.
It's actually putting codes and information into materials.
So phones were analog, Claude Shannon
wrote the best thesis at MIT-- best master's thesis--
setting up the idea of digital communication.
Now we have the internet.
And the key distinction is he showed
that, even though the phone can be unreliable,
by communicating in symbols, you can find errors and fix them.
So you can work perfectly even though the devices
are imperfect.
Then MIT had one of the last great analog computers
made by Vannevar Bush.
This was a room full of gears and pulleys,
and the longer it ran, the worse the answer was.
And so a bigger group of people digitized computing,
and showed you could compute reliably,
even though the computer was unreliable,
by computing with symbols.
Manufacturing today is still analog.
State of the art airplanes, chips, the information
is in the computer, not the material, so errors accumulate.
If you think about a child building LEGO bricks,
the LEGO is more accurate than the child,
because it corrects errors.
And when you're done, you don't put it in the trash,
you reuse it.
And you don't need a ruler, because the bricks
have coordinates.
There is information in the material.
So that's not a new idea.
It's four billion years old.
It's how you're made.
It's how the proteins in your body build you.
There's a protein, called the ribosome,
that builds with molecular LEGO in exactly that same way.
So the parts are more accurate than the things that
assemble them, because the material
itself contains information.
And so what all of this is leading up to
is about a 20 year research roadmap
to the Star Trek replicator.
Quite literally.
And the recognition that that's a problem in putting codes
and computing into material.
Embodying information in materials, to let them
turn into anything.
So to get there, our research is going in stages.
From computers controlling machines,
to where we're making machines that
make machines-- machines that can make their own parts--
to building ways to assemble.
You can think of it as engineering LEGO.
And at that stage, we're building nanoassemblers
that snap proteins together.
We're building micro assemblers for electronics.
Up to where we're building assemblers
to make jumbo jets out of giant carbon fiber pieces.
But assembling discrete materials.
And you can think of this as what comes after 3D printing.
And then ultimately, we're working
on programming the materials.
So that there is no machine.
The materials themselves change shape.
And to do that, again, we're doing
that across length scales.
From proteins up to buildings.
And in the middle of that range, then comes the work
for today, which is robots.
Today, to make a robot, it's a lot of work
to make all the different parts of it.
What we asked is, could we make robots
that you can make as one continuous thing,
and have it change its shape?
So shape changing robots.
And to do that we had to do three things.
We had to work out the mathematics of how you change
shape, we had to work out a new way
to actuate-- so that the robot can change its shape,
can move-- and we had to work out
a new architecture for a robot that's essentially
one long continuous piece, and doesn't
have the conventional separation into moving parts.
So what Ar's going to present is a particular embodiment--
this milli-motein-- but really, you
should view that as an embodiment
of three different things.
The math, the actuation, and the architecture.
And this is a version using it.
And in turn, it's part of this wider sweep
in making shape changing materials
across many different length scales.
OK?
So with that I'll hand off to Ara.
All right.
So first of all I'm delighted to be here, so thank you.
So we started this project.
We were inspired, as Neil said, by this idea
of programmable matter.
And for me, what that meant was, what's
called the bag of stuff problem in the robotics literature.
Which means you have a bag, and it's full of modules,
and you go and you reach into the bag,
and you pull something out, like, you pull out
a coffee cup, or you pull out a wrench, or something like that.
You use it, when you're done with it
you put it back into the bag, and the modules break apart
or unfold the chain, and now you can make your next object
that you need.
So there's no more trash.
Very nice vision.
So biology, as Neil says, provides us with the existence
proof that this is possible.
And I'm going to press my slide advancing button,
and am just going to use my computer.
So this is a video, made by my colleague Jonathan Bachrach,
and it shows a mechanical protein, made of modules here,
folding into shapes.
So each one of those modules has a motor in it,
and the ability to exert a torque to make a shape.
And you see it made a plus sign there, folds back into a line,
and then folds into the next shape.
And so we were excited to make this.
Really make this a reality.
And we wanted to make it small.
In one part, because the grant we
had said that the modules had to be at least
smaller than one cubic centimeter.
It couldn't be any bigger than that.
If it was bigger than that, it wouldn't really
be miniature enough.
And so this was the state of the art at the time.
And so you see the polybot here.
These robots are much more capable than the one
that we've built, but they are also
a lot bigger, and more complicated,
and more expensive.
So this is the polybot, which can turn its joints here,
and this can dock there.
This is the M-TRAN, that can walk around.
You can put the modules together and it will walk around.
This is a crystalline robot.
Slightly different.
So these are typical modular robots.
And then, because we all want to make this small,
we know that electronic components are usually
much smaller than mechanical components.
And so people have worked on, can you
make a modular robot purely with electronics?
With just electric and magnetic fields to provide the motion.
And so these are some examples of some systems that
have electromagnets on them, roll over each other,
these cubes pull toward each other with fluidic forces,
and so forth.
And so inspired by this, we wanted to design something,
but we wanted to design something that was a chain.
This is just showing that electronic components
are typically smaller than mechanical components.
So we wanted to design a chain, made all of electronics,
that could fold itself into arbitrary shapes.
Just like the video I showed.
And so this is the machine that we've built.
It's a chain of interlocked motor rotors, and stators,
and then it has flex circuit wrapped around it
for the electronics.
It's much simpler, and has a much smaller number
of components, than an equivalent four joint robot.
Power comes in along here, routes through, and comes out.
Now, when we started designing this,
we said, we're not going to use any gears.
Because if we use gears there's going
to be tons of bearings in there, and bearing
balls, and lots of teeth on the gears that can break off.
So we said, no gears, it has to be direct drive.
Well, we looked for a motor that would fit into this space
here-- which that's about the size of a dime--
and we couldn't find any off the shelf motors that would provide
enough torque to actually be able to move these joints,
without burning themselves up.
So we invented a new kind of motor
called an electropermanent motor.
And I will explain this, but before I tell you about that
let me tell you about the math of forming
these shapes for a minute.
So I told you before that we could fold arbitrary
shapes using this chain, and that's
not a super intuitive concept.
So let me explain how that works.
Let's say I have this dog, and I want
to make this dog using my folding chain, right?
How do I make this dog?
Well, first of all I make a pixelated representation
of the dog.
And then you can make a spanning tree here
that encompasses the whole dog.
But if you were going to use a robot like this
it would need to be able to have T-branches in it,
and that would be complicated.
But if you divide the pixels up, so each pixel breaks up
into four pixels here, then what you can do
is you can just wrap one long continuous chain around it.
And you can fill all the space of the dog.
And now you can have a-- just like we
were showing earlier-- you can have a chain that folds up
into a dog.
So this is the math behind this.
And we have proven that any-- and you
can see the basis of this, here-- that any shape--
including in three dimensions-- any shape,
you can make it using just a chain folded like this.
And one of the nice things about this is that all this is is,
as you advance along the chain, you fold left,
or you fold right, or you go straight,
and those are the three steps.
So those-- left, right, and straight-- are, if you like,
the DNA code for the object.
And then you can fold your mechanical protein
into the shape based on that code.
So when we were building this chain, as I said,
we couldn't find any motors that would
do the job without burning out.
Unless there were gears, but we didn't want to use gears.
So we invented a new kind of motor
called the electropermanent stepper.
And that's based on an electropermanent magnet, which
is a type of magnet used in steel mills--
and also in telephone switches, as it turns out--
that doesn't require any power.
You can switch it on and off.
So like an electromagnet, you can switch it on and off
with electricity.
But like a permanent magnet, it doesn't require any power
to stay on, it doesn't require any power to stay off.
So it's a wonderful hybrid of an electromagnet
and a permanent magnet.
And I have a little-- the basic concept of this
is just that you have two pieces of magnetic material in here.
One, it's very hard to change it's magnetization,
and one is very easy to change its magnetization.
And so if they're magnetized opposite ways,
then all the field stays inside, and there's no force down here.
But if you apply a pulse of current,
you can change the magnetization of the weak material.
And now they're magnetized the same way and it picks up.
And whether it's on, or off, it doesn't take any power.
So we built a motor around this, where
we took each one of these legs of this arm,
here-- each one of the legs of this object
here are electropermanent magnets,
with a strong magnet and a weak magnet in parallel,
with a coil wrapped around them.
And this is a motor called the wobble motor.
So what happens is this center part here stays stationary,
and these two legs will be attached.
And then when it takes a step, these two legs
will be attached, and it turns around.
So I can show a video here of this motor turning on my desk.
We did some initial testing of-- this
is an earlier version of-- the drive circuit.
And you can see it rotating around there,
so we were excited by this.
And so then we went on to design the rest of the system
around this motor.
So we have our electronics.
The electronics are very simple.
Power and data come in, there's a microprocessor--
which is right here-- there's some energy
storage in these capacitors-- right here-- there's some power
electronics to drive the motor, and that's it.
Power and data goes out, to go to the next module.
So this is the circuit that wraps
around each one of the modules.
So we built a module.
And I think this was about 2 o'clock in the morning,
testing this on my desk in the handle of a pair of scissors.
We had to learn-- myself and the other graduate students
that worked on this had to learn-- watchmaking techniques
to put this together with tweezers under the microscope.
A vendor we had been talking to, about something, told
us this cool term, which he called, oh,
how are you going to put that together?
And we said, oh, we're going to use-- he said,
you should use GSWT technology to put that together.
And we said, oh, cool, what's that?
And he said, graduate student with tweezers.
Oh no.
So we got this put together, and then went ahead and designed--
well, once we had that together, then
we went through and did a lot of work to make it reliable,
and be able to put four of them together.
So this is just showing how this is put together.
There's that motor core in the middle,
there's some ball bearings on here,
the case that goes around it, and that's pretty much it.
And then the circuit wraps around,
and goes on to the next module.
So here's some results.
Shape reconfiguration results.
So you can see we had this four unit module,
and we have it here in a line, and then
we can send data in to tell each one of these modules what
angle to turn to.
And if we just turn the last one here,
we can configure it into this L-shape.
If we turn this one, and this one,
we can configure it into this periscope.
Or if we turn all three of them, we can turn it into a helix.
So the code is just left, right, or straight for each
of these three.
And with these four modules, we've made these objects.
So I'll show you a video of that.
There it goes.
The power and data come in here, give it commands,
folds into a shape, folds back.
Now, when we were working with this,
we did some tests of the amount of torque
that each one of these can hold.
Because of course, one of the big questions
we were trying to ask with this is, is it
possible to build a robot that can change shape,
but without using gears.
Just having magnetic fields directly drive the axes.
And we found that, yes, it is possible,
but we were only able to get a cantilever lifting
strength of one, we call it.
Which means that if you hold this robot out in a chain,
and this is the last module here,
that we can lift one module up as a cantilever,
but we can't lift two or three modules up as a cantilever.
Now, the macroscopic geared systems
I was showing earlier usually can lift two or three modules
as a cantilever.
Not much more than that.
And we think we can get it stronger
in the future with lighter materials and better magnetics.
But but here it is.
It's working, and we think it's the smallest,
highest resolution modular robot yet made.
And is just the graph showing the torque results
I was talking about.
So we're really excited that it seems
like we have a very low power count, scalable way to build
these shape changing chains.
But graduate student with tweezers is not going to do it.
I really hope that's not the future.
And so what is the future?
Well, one way to do it, which is something
that our lab is working on a lot right now,
is an automated assembler.
Having a machine that can take lots of little parts,
conceptually that are like LEGOs,
and put them together to form something like this.
And you might think of that machine forming the shape
that you want, like forming your coffee cup or your wrench.
Or you might think about, on a smaller
scale, that machine being used to build things like this.
And then the other thing you could think about
is an integrated additive process.
Meaning, current technologies for building
micro mechanical systems are not up to building something
like this, but could we invent some better processes,
that can deposit a greater variety of materials,
so that you really could build something
like this in one shot.
With MEMS technology, additive fabrication,
that kind of thing.
So those are the things that we're interested in now.
And I'll also say that as we went along doing this,
something we found was that this motor was actually
immediately interesting for commercial application.
So a small, low power, high torque motor, it turns out
there's a lot of aerospace and medical applications for that.
And we're working with some industrial partners
right now, to try to commercialize this, and get
this out into the real world.
So thank you very much.
[APPLAUSE]