- [Announcer] And this is an honorable mention winner.
- Okay, can I use this?
Thanks.
Hi, I'm Sang from Fluid Interfaces Group,
a multimedia lab, and I'll be presenting
Body Integrated Programmable Joints Interface.
It sounds very complicated,
but, in short, what I'm trying to do is
to make cyborgs happen.
And, yes, the notion of cyborb
is very quite familiar with us,
especially as we see from many sci-fi movies and literature.
And they're often presented as prosthetic technology
or some sort of augmentation technology
that gives superpowers to people.
And, of course, many speculations around cyborgs
are depicted as somewhat dystopian,
like this is our biological body taken over
by very scary electromechanical devices
or becoming a superpowered villain trying
to destroy the entire New York City.
And even without going that far,
it is true that sometimes technologies
that we use are somehow designed to carry us away
from what we used to think as valuable.
And as McLuhan pointed out,
there may be no augmentation without amputation.
So our driving question was:
can we then create cyborg technologies
that does not replace our original capability
or that doesn't enforce overuse of it?
And how can we design machines that more form
of a symbiosis with us instead of substituting
or removing the role of our biological body?
So in order to explore that,
we prototyped a wearable robotic device and applications
that highlight more synergetic interactions
between human and machine body parts.
And this is a quick peek into, sorry.
Into what our robot looks like.
It's made of 11 servomotors linked to each other,
and it affords basically a physically reconfiguring
machine body to the wearer.
Before going into to details,
I like to zoom out a little bit
and talk about related works briefly.
Of course, we need to mention the artist Stelarc here.
He has envisioned and implemented actual integrations
of human and machine bodies for himself for long time
and brought in this notion of evolution driven
by human-machine symbiosis.
And there also various forms of human-machine integrations,
especially from the field of robotics,
and we will classify them into three groups:
prostheses, exoskeletons, and supernumerary robots.
Prosthetic robots are designed to replace
or supplement the body part,
for example, for people who have loss of limbs,
and, therefore, their main goal is
to closely replicate the forms and functions
of our biological limbs.
And exoskeletons, on the other hand,
are designed to enhance a person's physical capability
on the basis of existing body structure.
And through external structure support provided
by exoskeleton robots, they're designed to amplify the users
to have enhanced strength or speed,
as you can see from the interesting names
of these projects here.
And these are some notable recent works.
BLEEX from Berkeley has amazing work.
Hugh Herr works for MIT Media Lab, is also very notable.
And this full-body exoskeleton HAL looks also very cool.
And lastly, supernumerary robots.
They are designed to give additional number of limbs
instead of replacing or enhancing existing ones.
So, this is a new field actually.
And this exciting new field of research explores
the cooperative integration between humans and robots.
However, still if you look at the works there,
the forms and utilities of these robots are limited
to replicating human limbs or fingers.
So, but we believe that a fully re-configurable
and programmable robotic wearable can really open up
a huge design and attraction space
beyond just having additional number of limbs.
And this is one of the main things we set out
to explore in this paper.
And these are some example applications
of our programmable joint system, the robotic wearable.
And we show, this can support multiple uses
by simply reconfiguring to different shapes and motions.
And one other notable feature is
that when the user doesn't need the function of this robot,
the robot joints can turn
into wristband kind of configuration
and disengage from the user's context.
So, it doesn't enforce the continuous use of the robotics
and only comes to foreground when the user needs it.
And you can see me using this wrist kind just to activate
and de-active the engagement of the robotics.
Then, how is it controlled?
We are using EMG singals, picked up from the forearm,
like here, and as you can probably see in the video,
the robot can be controlled separately
from my hand gestures.
It is because EMG signal we are picking up has
a very low correlation with other hand gestures,
so that basically you can have separate control
over the machine joints and the biological fingers,
at the same time.
We'll come back to this later, briefly in this talk, later.
Then, what are the possible applications
with this kind of robotic, transforming wearable?
And here we present three of categories we identified:
So-called synergistic action, background synergy,
and interface support.
Synergistic action describes a collaborative form
of a cohort between the machine fingers and human fingers.
And for example, as you can see here,
Yeah, (laughs)
the machine fingers can hold objects for you.
So when you need room for other actions or interactions,
you can text a friend while you're coming back
from grocery, without too much problem.
Or if you can have, if you have an opposable palm
instead of opposable thumb, you can like grab a basketball
only with one hand, which is actually pretty hard.
And background synergy, describes more passive types of,
type of assistance robot, like for example,
like in this one-handed note-taking example.
The robot provides the structure of support,
so you don't need to use two hands to achieve
these body manual tasks.
The robot will do the rest for you.
And, one other interesting application domain we found,
is interface support where the robot is used
as haptic controllers, like a joystick or a gun interface.
And this can especially be very handy
for VR applications or gaming.
Also, because, the motion of the robots
are totally programmable, it's possible to render different
dynamic physical properties, like the recoil speed
or shooting speed of the gun in a VR shooter's game.
So you can have a lot of fun in that.
So coming back to the muscle-based control,
to figure out how to control these additional machine body
separately from our biological body,
we conducted a user study and measured a correlation
between EMG signals from each part
of the my-yool arm-bend we used.
And tried to find how much they are correlated
with different hand gestures.
We used the hand gestures, shown there, in the slide.
And the EMG signal picked up from a muscle,
like an oh-call brachioradialis,
is shown to have a regular bell correlation.
It's sensor location D, over there.
And it means that, we could use that signal
for controlling the robotic joints.
And you can use it to independently control
the machine joints using this muscle activity,
if you learn how to use that,
independently from the biological fingers.
You can see I'm controlling the machine joints
and fingers all together, only the machine finger,
and the biological finger.
And it will also be interesting to see, to which extent,
we can learn how to control these machine-extended bodies.
This experiment from University of Pittsburgh,
shows that--it's not about humans,
it's the study with monkeys--
shows that in just two days a monkey could unlearn
how to use its biological arms
and learn how to use a very high, complex robotic arm
using his brain signals.
So, my remaining questions are, to what degree,
then, this would be applicable to us
and is our brain really plastic enough
to accommodate more complicated, like in the body forms.
And if that's possible, even in that case,
what would be the optimal way to map body signals
to such machine control?
We hope our work to be the starting point
of these interesting discussions
and hope to find more answers through following works.
And this is the conclusion slide that I prepared,
but this afternoon, after Alan Kay's event, I decided
to rather leave you with this quote from Alan Kay.
Thank you very much.
(audience applause)