so if you could just start by telling us
your name where you were born where you
grew up and
went to school my name is ayanna howard
i grew up in pasadena california
i went to undergrad at brown university
in graduate school
at the university of southern california
when did you first become interested in
robotics i became interested in robotics
in middle school
um so it was sixth grade i was
interested
in sci-fi so sci-fi was all the rage
and they were starting to show women in
positive light so wonder woman
and my favorite was bionic woman and so
i
i knew when i saw it i was like i wanted
to
build a bionic woman in fact if you
looked at it you know she was cool
she was bionic the engineers were a
little nerdy but that was okay so i
wanted to be a doctor
so i was going to be a medical doctor
and i was going to create the bionic
woman
um and then i took biology and
absolutely hated the cutting and so
i switched in terms of in fact it was a
teacher that said you know
you really want to create the bionics
you don't necessarily want to do the
operation
um so i knew then that i was going to go
into engineering computer science
something related to robotics
and what did you study at brown um i
studied
engineering um so technically computer
engineering
but brown has a level approach to
engineering which basically means you
take
a little bit of what's considered
mechanical a little bit of electrical a
little bit of computer engineering
and then you decide based on your
courses which you want to take in junior
and senior year
so i was general education and
engineering but i consider myself
computer engineer
and what was the first robotics project
that you worked on or did you work on
any robotics project
yes my very first robotics project was
actually my sophomore year in college i
worked with a professor
who was a robotics guy and i did
manipulation so
at the time worked on coding a robot
arm to trace around objects to then
figure out what the object was
which you know the time was like oh you
just program it you approach
you know didn't realize that was
actually cutting edge at the time
great um and then what made you decide
to go on to graduate school
um so i knew i was going to go for a
master's and this is because i
after my freshman year i started working
at nasa jpl
um and so everyone at nasa either had
had a graduate education either masters
or phd so i knew i was going to at least
get a masters
in fact that was all i thought i was
going to get because i actually wanted
to
you know have a real job and make some
money
um but when i went into grad school it
was just so different than undergrad
and it was so fun it was like well
there's a robotics course okay
oh i'm doing robotics research okay oh
there's a robotics person coming to give
a talk
i mean it was perfect um so i decided to
stay
what were you doing at jpl before grad
school
um so i worked at jpl
also well i was there basically i worked
there for 20 to 30 hours
and also was a student which i don't
recommend to anyone
what kind of group were you working with
um so at jpl that's when i got
interested in artificial intelligence
and learning and interacting with people
so i was a controls person so i was
you know i learned about feedback
control and adaptive and i was controls
but with nasa jpl what we started to
look at was neural networks
how do you take this data and do data
mining
and all these interesting things and so
i consider myself
a undercover computer scientist because
of that
did not take a formal computer science
course until grad school
basically because i said i've been doing
a lot of programming maybe i should
actually
have some formal education on this uh
but self-taught computer science because
of the whole nasa experience
great and what brought any projects in
particular that you remember
um so when i started off what i worked
on was
actually pretty boring converting
fortran to c
uh for some of the satellite data so
that was my very first project
and then went on to work on robot
manipulation
worked on when i before i left actually
worked on
mars exploration projects so designing
advanced technologies
primarily to model how people navigate
and how scientists interact
figuring out how you take that and code
it on a future mars rover
and who are some of the people you
collaborated with um
so some of the people were one was my
advisor homie and sarajee
um he passed away and then other people
who were in my group there was issa
nesnus
eddie tunstall worked a little bit with
volpe who is actually now
the section manager of the robotics
larry matthews was a project manager
sometime curtis padgett
supervised some of my projects um
i think those were the major ones uh
jacob barton who actually went to
um oak ridge he was one of my first
supervisors
i was curious who the professor was it
brown that you
that you were wadovich
and so you decided to go to the
university of southern california
um yes uh mainly because they had a
really good relationship with nasa
um in fact the usc we there was trailers
at jpl
that advertised the courses and this was
before the whole
moocs and things so you could go up in
the trailer
and actually take the course remotely
so that was just like a no-brainer i
could actually work at jpl
still take my courses at usc um
so usc was was just great for that
and they had some good professors and
who were the professors you worked with
um so actually my first advisor was ken
goldberg
um so he had started off at usc and in
my
in fact he was my first research advisor
and then my second year there
he decided to leave so that was a
transition point do you
go or and i had already passed the
qualifying exam
so that's that's a big thing do you go
and have to retake everything or do you
just
say stay find another advisor and so we
started off he was going to co-advise me
and my primary advisor became george
becky
and so eventually what happened george
becky became the advisor and so i
graduated with george becky
and what was your thesis projects or
projects
so my my thesis project and no i didn't
do a master's
i'll you at usc you can request a
master's
so i requested it just basically i have
enough units yeah
so my phd project was on
figuring out how to enable a robot
manipulator
to sort out waste for hospitals
so the concept was at this time this is
when there was a big
concern about things like hiv and
needles
and the hospitals hadn't gotten into the
security so right now you go to a
hospital
you know needles go into this metal bin
everything is safe so back then it
wasn't quite the same
and so my task was how do you have a
robot
go in and figure out what's the bag of
needles
versus the bag of fluffy
sheets versus trash and how do you sort
these with this waist out so that
humans don't get hurt so learn
things like vision you know because you
have to figure out the
shapes put in some of my control in
terms of deformation so if you grab some
of these things
you know it deforms based on what's in
it um can you learn that characteristic
and then how do you grab it so it
deforms that means you have to have
different points of inflection
and torque in terms of grabbing it so
where should you actually grab it so i
had two arms two manipulators
that would go and they were basically
just like a little kid would go and
squeeze it a little bit come up with a
model of okay what was most likely in it
given that this is most likely in it
where is the best point to grab it
underneath two sides pick it up things
like that so that was my thesis project
great and um so they kept working on jpl
i did it was just i basically uh on
monday
i was 20 at that time it was actually 30
hours
you know by friday i was 40 hours so it
was it was
not even a working ad it was just i just
changed the number of hours
uh that i worked and did you collaborate
with other
graduate students or faculty at the usc
during that period um so i had my
my lab mates um so we weren't ever on
any of the same projects but they're
your lab mates so you see them every day
you cry on their shoulders they come to
your defense
and so my lab mates were in fact
some of them were still in academia so
there was
um sergio miletios who's at
university of minnesota now
there was jim montgomery who
works with nasa there's alberta bihar
who was at nasa that just passed away a
week ago
there was um
i think who tall guy mike mchenry
who was at nasa he left then i have
um tony what's tony's last name
tony lewis at qualcomm tony lewis who's
now at qualcomm
he was my boss oh really
okay seeing small world i'm like i
couldn't i
was like what's his last name
so okay and he's doing very well at
qualcomm yeah
yes um
and um so then what kinds of projects
did you start working on
following the phd um so
so the ones i was talking about but um
so immediately after the phd i kind of
um started because now i had a phd i
must know what i'm doing
um i started managing my own jobs and
writing grants and so
my first big project
was designing navigation algorithms for
robots
um based on trying to figure out what's
in the train
um so at the time was train assessment
so if i see a train can i figure out
you know what's rocks what's cliffs um
can i tell the difference of the texture
of the ground so if it's sand versus
hard ground because you want to change
your navigation profile so i was
incorporating vision along with learning
along with fuzzy logic to classify the
train and then put that into your
controller so that as you navigate
you can use this information to change
how you might
roll on the surface so that was one of
the very first projects
and then some of that same technology
started and was transferred to trying to
figure out how to land safely on mars
so you're landing you want to do the
same thing as you're descending you look
at the train
you have a very large area that you want
to descend
and you don't have precise information
till you get there and so how can you
use that information about the train and
from your sensors and
come up in basically real time an
assessment of
what's the best place to land and how do
i get there so
in that aspect if some of it is maybe
the safest place
you can't get to safely and so what's
the next safest place and so
again combining things like terrain
assessment vision control in that case
as well
um because you have to understand things
like you also have measurements on
you're there now you know what's the
quote-unquote wind speed for example
and how does that equate in terms of
where you can navigate to
um so worked on safe landing um
and then so those were like the two big
projects that related to the mars
exploration program
but then some of the side projects i
actually enjoyed that i did
was doing things like designing a
hardware sensor
so one of the things i'm interested in
is so all of this was software-based so
this learning and this navigation
can we somehow encode some of this logic
very very specific
you know and make a sensor so one was a
traversability sensor
you know we're doing all this train
assessment can we just take that code
and put it on a sensor and it basically
gives you a value from zero to one
so that doesn't take away from all the
other logic that's going on all of the
other
information that has to be processed so
i started dabbling a little bit in terms
of
designing sensors designing little
modules of ai components that you could
play on say like an fpga
so different things just kind of
exploring so those are my call my pet
projects
and did some of those wind up on any of
the rovers none of my stuff
ended up on any of the rovers so why is
that
so what happens is the way that
research works is you have maybe four or
five competing ideas
and it's not necessarily not to say mine
wasn't the best but it's not necessarily
which is the best it's the one that is
validated as the most safest
at the time that they need it um and so
if you have a mission let's say 10 years
away
they need it they need to know that it's
going to be 90 reliable within the
specifications
you know basically 10 years before it
happens um and so
and as researchers we don't even we
don't even compete that way
um so you just keep going and then
someone's like hey are you guys ready
you're like no i need some more testing
and then they go to the next research oh
you guys ready
and so eventually that is what happens
and so with my stuff i left before
so my mission would have been msl and so
i
left right when it would have been put
in
but if you notice msl does thing it did
things like
change where was going based on train
assessment so not to say anything
but uh those ideas and those thoughts
were definitely
started to put into the missions
um so i decided to leave jpl because
um there was a shuttle accident and at
that point
nasa basically i won't say zeroed out
research funding but they
pretty much halted um anything that was
beyond
the immediate horizon and so at that
point i had to decide do i just rough it
out
you know figure it out or you know what
is it that i really like did i
like jpl or nasa or did i like research
um and i decided that research was more
important than robotics research
and so i decided that i go where the
research is and
at the time academia was where research
was still
you know prevailing um you didn't have
to fight as much in terms of the nasa
money
um and you had other fights but you
could still do research
so that's why and so what was the period
of time that you were at jpl
um so i was actually my my very first
summer was the summer of 94.
um i became full time so a full-time
employee 40 hours and 99
and i left in 2005.
so i was going to be a lifer i mean
there was everyone so surprised when i
left it's like you're a lifer
where are you going um but it was a good
decision
and when did you go i went to georgia
tech
so i went to georgia tech in 2005 i
started there in july
and it's been a great experience it's
been different but
definitely a great experience at which
department are you in there i'm in the
school of electrical and computer
engineering
um also part of we have a robotics
institute
so i'm also a part of the robotics
institute and
i think they call me associate director
of research which means i do something
with research with the institute
it was the robotics institute already
there when you came in no so when i
started there was no robotic center
there was no robotics institute
um there was no robotics phd program um
so i was i would say
the first of trying and so georgia tech
has always had robotics
has had good robotics people um and so
um when i came and the reason one of the
reasons that they hired me is they were
just starting to think about
you know how do you synergize the folks
here how do you grow
that robotics edge so i was one of the
first
kind of strategic thoughts about how to
do this
so i was on the committee that got i was
on the phd committee so i was there
you know pushing it through the system
so i was there for the first class
i was the second director of the phd
program
um so was there the institute we're the
ones that interviewed henrik
christensen so you know i'm sitting with
the other faculty
you know interviewing you know who's
going to be the director of this new
center
so yeah i was there before it existed um
and i i came i think at the right time
at the beginning of the growth which is
nice because you have a lot more control
about
where it's going well who were the other
roboticists that were there when you
arrived
um so magnus edgar stead was there he
still is there
uh wayne book who just retired but he's
still there
um ron arkin um who's still there
uh tucker bulge um frank dellert
and um aaron bobbik
he's um robotics more heavy on ai
but he's considered now he's he's
totally robotics but at the time he was
ai
like oh yeah this robotics is
interesting um
so those were uh the main folks i'm sure
i'm forgetting
people but those are the ones that were
actively engaged
at the beginning what were the big
challenges to setting up a phd program
in robotics in an institute and that's
very
interdisciplinary yes um
interdisciplinary is the key um so
for the phd program um the hardest
challenge was
that you have and even in discipline you
have different cultures so computer
science has a different culture than
engineering and in engineering
electrical has a different culture the
mechanical then
aerospace then bme biomedical so those
are all the five colleges
um and so how do you position
a degree where you have different
characteristics
different culture even different
requirements that the faculty are used
to
so that's it's really trying to convince
the faculty because
academia is really is driven through
grassroots it's the faculty that get
together
and they push it through typically
unless it's a strategic initiative it
doesn't come from the president says
thou
shalt because faculty we can say no and
we have every right to and we do
sometimes
so it has to be grassroot so i think for
the phd
it was making sure that we had a good
story
making sure we had a reason for this and
making sure that our graduates were the
best that they could be and that they
and we we forced it very carefully and
we've had to change things
to make sure that they aren't
interdisciplinary so every robotics phd
student comes out
they've touched some aspect of
engineering as well as computer science
so they've programmed but they've also
they've taken control for example
or they've taken mechanics and so we
force that and maybe they
stay in computer science when they
graduate but they understand
oh there's other parts of the robotics
equation um and they're not limited
which makes
i think what's valuable about the phd
but also
makes it a little challenging as well
and so what are some of the projects
that you lab worked on
at georgia tech oh so georgia tech um
it was a good start
um so at georgia tech one of the
difference between
being academia versus at a research lab
is that your projects are your own
um so pretty much you work whatever is
in your head
you work on um so when i first started
at georgia tech i had to figure out what
i knew was nasa what i knew was
exploration
so how do you do that when i don't have
a rover in my georgia tech lab
um so that was the first challenge so
looking at the problems because i know
scientists and so
just figuring out what is it that i
could do as an academic um and still
have an impact on exploration
so i actually built an indoor mars yard
um
and interacted with scientists and earth
scientists
because that's what i'm here on earth i
can send rovers to
places on earth um so
grants grants grants but grants grants
grants so my very first
uh project was uh sponsored by nasa but
the earth science division
and we were sending rovers to glaciers
to understand climate change
and this is right at the beginning when
um you know there was the gore
the whole gore book and and things like
that so it was it was it was a nice
place to be it's like oh we rovers that
we do it on mars we can do it here on
earth
um so we actually went to glaciers um in
alaska in colorado there's a glacier in
colorado
um so we grabbed built rovers
basically hacked toy mobiles
so basically the little mobiles but
child size
we hacked those made them autonomous put
cameras on them put
intelligence on them um science
instruments on it and we would
so on the technology side it's it's how
do you create this integrated system
low cost with all these sensors that's
autonomous on the science side
it's how do you get this data and make
it in a form
that's representative so how do you
create a sensor map or a data map of
information
that's also localized exactly to where
you need because scientists
need very high precision which we need
and rovers too localization so it was a
nice blend
so that was my very first project from
scratch so it was the first time i
actually had to build something from an
idea
very challenging but at the end we had a
great
asset that could be used um and unlike
nasa though it's like when the funding
runs out
you either continue or you decide to do
something else so
did a little bit more but then
translated that a little bit i decided
what is it that i really enjoy in life
um and i i love nasa i loved exploration
um but it was so hard doing that
and at the end i mean we had cool media
we were you know usa
today and things like that but at the
end i had to think about
if i can do anything because that's what
i can you can do anything
in the world that you want what is it
that you want
and so i decided to revert back to my
thesis
and go back into the healthcare and so
um toward the end of the when i was
working on the glaciers and i still do
some exploration so
we said now robots undersea in fact i
had a student come from antarctica
sending a undersea robot to do some of
the mapping so still do that
much much smaller scale but started
working in healthcare and children with
disabilities
so designing robots and associated
technologies
assessment methods to
enable robots to do therapy in the home
with kids
so again anything that you want what is
it that you want and that was
what came now if you had asked me you
know exactly then you know okay what is
it it's like i don't know so i just
started doing it worked a little with
this you know kind of the ideas in my
head
um and that was what really hit home
um and what was the first project what
did you build
so the first project um we call it
playing with toys got a small grant
worked with actually charlie kemp on
that one
because he was at the time he was
healthcare um
not kids but he was healthcare and so i
used his equipment
because i'm not sure what i wanted to do
but playing with toys was can i
model so can i look at a child or an
adult or a therapist
and model how you're playing and
interacting with toys
and take that information and have the
robot play in the same way
so that was a project and so um that's
when i got into this whole so
i realized i'd done human robot
interaction
all of my life but was never classified
as hri in fact because you know hr is
pretty young but i'd always work with
scientists and learning from people and
trying to encode that knowledge
in fact my lab was called you know
humanized intelligence it was like in
one of my papers it was like we're doing
humanized intelligence
um and so and this is when you know hri
started i was like oh i guess i sort of
do hri but
from a different perspective because
it's again from that classical
controls per se perspective and we're
using humans more as and i think of it
as
if you have a control law the human
could be your input
or it could be your disturbance vector
and so
looking at the human at as that point is
is
how i looked at the equation now my
perspective is totally different
but at the time when i first started it
was just like the human is just
a box in my controller and it can infect
it can be my input or it can be this
thing
that's an anomaly and i have to figure
out how do i navigate and it's just a
disturbance and positive or negative but
there's some boundary conditions
it just seems so reasonable and so
logical at this point
uh and it totally fails in the real
world um
so that was basically the approach and
so
first system we that's when i learned
about irbs and you know doing human
subjects because
at nasa you just ask your friends to
come and you know okay i need you to
code up this okay i'm going to take your
data and then academia
is like oh no it doesn't work quite that
that way
um so first system and i totally enjoyed
it i think i enjoyed
having to learn something new and so i
mean
we're the expert and a lot of times what
we're learning
is just a little deviation of what we
already know so you read another paper
it's like oh that's an interesting
perspective i'll code that out
but here was a case where it was
entirely new i had to understand
what is this aspect of real learning
from people
um what is this aspect of play because i
wanted to play for therapy
so started interacting with clinicians
and therapists and actually sitting in
therapy sessions
with clinicians and kids to figure out
okay what is really the problem i have
this idea in my head
looks good on paper we got funding for
it but you know what is it like in the
real world
um and i think i enjoyed the learning
something new
and then being able to take that and it
was just like being
back in your thesis but without the pain
so like all of the joy of discovery um
and doing that and
so when i we finished that project i was
like
this is this is what i want to do um and
so since then
we're it's been amazing it's been
amazing
you see these kids their eyes light up
you're actually seeing
some some aspects of improvement in
terms of therapy using
your technology we're now
commercializing some so have a startup
that's commercializing some of this lab
stuff
and it's just an amazing thing to
actually see that you know all these
years what you've been doing
can actually help someone besides mars
was it really challenging the first time
to work with children on a robot
together oh yes you learned so much um
when so the first thing that i've
learned is
uh when you're designing technology
introduce it to your target demographic
before it's ready because
and again this is lessons learned so now
i know it's like it doesn't have to be
ready
you just need to see if you're on the
right track um so i remember
our first first thing we were going to
do was using vision
so we're going to use it was the connect
so we're going to use the connect
to um grab some of the the data the
structure because we need to come up
with kinematics
so we had this full system it worked
perfectly with all of our
you know human adults which are students
and it was it was great
um and then we took it into the first
and of course the lighting conditions
we had already figured that out so we go
into a home
and we have a child severe disability in
a wheelchair
that's sitting there very patient and we
cut on the system
there was no child in our imagery it's
like oh maybe it's the lighting and so
of course you have this child in a
wheelchair we're like
you know we're gonna move you around we
move furniture around
and you know all of these things still
didn't work
so here we are our first subject
child with cp very
very very generous nonverbal but very
jealous very excited
and so we actually got it to work the
dad picked him up put him in his lap
and suddenly he saw the child like
it makes no sense right so again now
he's playing the game
and we're having this little so worked
out so then of course you're like okay
so why didn't it work
so we go back and it's little things of
the fact that
you know typically you have typical kids
you have adults
none of them are in wheelchairs we have
them sit in chairs a chair looks
actually different in a camera than a
wheelchair something very simple that
you wouldn't know
until you and then there was other
things that that quite didn't work the
way we
intended um and you don't know until you
actually have
whoever it is that you want to use the
system they're
testing it out so yeah we've learned
that was just a little thing but we've
we've learned
quite a bit not everything works but
it's okay
and do the kids get over excited about
the robots and does that interfere
the kids definitely get overly excited
about the robots um
but i will say that that's okay
because it works
and so um what we find is we actually
want the extremes because the extremes
if our system works at the extremes
it's going to work for everything in
between so a child who's excited
who doesn't listen who doesn't actually
follow the nice trajectory like okay we
want you to follow the robot exactly
we're going to measure it and the child
does it
and the system still does something
right then that's a good thing
because that's going to be your extreme
and so one of the things that my lab
practices now
again is early introduction of the
technology to the child demographic and
there are no rules
um i.e there's a role in terms of the
protocol but there's no rules of what
the student do so we give general
instructions
like we like you to do this but there's
no correction like oh can you redo this
it's because this is what it's going to
be like in the real world
and um our systems now they work i mean
our latest we have a robot that
interacts with kids
children with autism as well as typical
kids with a tablet
and we've taken that robot to about
maybe 30 different places over 100
individuals and it works every single
time
any i could just bring it here i can
call and say hey let's bring the robot
let's cut it on
the only thing is sometimes the battery
wasn't charged and that's that's the max
um but we make sure that it works all
this time because
again that first instance with our first
child you don't know how
you're just like oh my gosh
they're so patient the parents are so
patient because it's something that
is needed so it's not just like a nice
novel idea
or it's like oh this is a beautiful
equation now this is actually a need
that's
is wanted and desired in this target
demographic and so
you know as a researcher you can
actually make a difference with your
robotic technology
so parents and kids are totally patient
with
robotic researchers when even when it
doesn't work quite right
and these are primarily diagnostic or
therapeutic
so these are so we don't do diagnosis
because we are not medically trained but
we do provide the data so that
clinicians can
actually come up with an assessment and
we do therapy so there's both parts of
equations
so we've done some evaluation fact we
have a paper out that shows that
our evaluation that the clinician can
use
is equivalent to
their standard measurements so they they
typically have
um basically tools where they can do
diagnosis
and so and they actually have to do and
they do measurements and do all these
things and
we show that our just have this
follow directions or not and we can give
the clinician
the same type of data for her or him to
make the evaluation
as the standard clinical tools
so that's one and then the therapy is in
the home can i gaze the child in moving
so that they can do repetition
repetition repetition
so so tell us a bit about your startup
and what that experience was like
so another learning experience brand new
it's like you have to learn everything
and i think
that's i think that's what excites me
which means in 10 years it'll be
something else
so so what happened was like so nsf has
this program called icor
which is basically
nsf gives academics a lot of money
and again three years maybe four if you
extend it but you basically
three years four years and then as
academics we're on the next grant and
then we're on the next grant
and hopefully we can have a continuation
but sometimes that that's just not
possible
um but typically most academics it stays
in the lab
so you do it and we get some beautiful
papers and our citation index is high
and everyone knows your name but if you
go out and
pick off you know just some random
person it's like oh do you know what
x has done they're like no but i saw
that robot on tv
and you're like yeah but that's fake
that's not real and so
what basically nsf was like we need to
get these academics to get this stuff
out of life because it's great stuff
i mean there's so much stuff i see on tv
out there i'm like that's crap
you know that so-and-so is like doing
this but it's not getting out of the lab
um and so the i course is basically take
academics and start looking at your
research and your technology to see is
there something that can translate
um and it's not about you know academics
go quit your daytime job
it's not about that it's just can you
translate the technology
um so participated in that and
our technology and it wasn't even a
robotics technology although
we are now transferring one of the
robotics technologies it was basically
an assistive technology
to be able to interact with robots so
these are children with cp
so primarily with children with cerebral
palsy with motor disabilities
how do you communicate to your robot and
we're using tablets how do you
communicate to the robot through a
tablet
now if i have a motor impairment you
know pinching and swiping
is not necessarily it's difficult very
difficult if not impossible
so how do i provide that so we designed
a
device that allows a child to use their
joystick
or use switches or whatever access point
they have whether it's their head
to control their tablet and then control
their robot so that device is what we
went through the high core program
and so from there what we found was
it wasn't about the robot people were
like oh yeah that's cute you know but
you know the tablet that that
interaction being able to
you know the thing was my child can use
this to you know navigate youtube
yeah but but no here's the robot right
so what we learned is is that that
interface was actually
something that was a good thing um so
that was the first technology that we
then translated so
process is how do you design a
technology
that works perfectly for you
in your lab and outside but you're still
there's
a grad student or a professor that's
still there so if anything
doesn't work like oh wait just a sec let
me reboot all right oh just a sec let me
do something um how do you take
something like that
and provide it so that someone basically
opens up their box
from amazon they plug it in and it works
every time and like oh this is obvious
that translation
is probably the hardest thing um to do
is making it so that it's so robust and
it's so
it's just like your iphone you don't you
don't expect your iphone to come
not charged it's just you get it you cut
it on
you transfer your number and it and it
works
if it doesn't work then it's like wait
this this is this is
this is not reasonable so how do you get
research to that stage
um it's a different way of looking at
things and thinking about things
what was the name of the company oh
xyrobotics
and so do you primarily do the software
are you doing some of the manufacturing
so we do it all um so we do
and when we say we do the manufacturing
so we um
have a electronics manufacturer so but
we did our
the whole um bomb or we did the
deliverables the cad and so basically
they have a list of the parts and so
they put it together now
i'm all the very very first units we
actually built in house
um you know with a very talented tech
that could solder and then we have
some basically software both for the
device
and we have some educational apps as
well math apps
um and again they're all designed to be
so typical child can use it but the
purpose is to
enable children with disabilities is
access to
these games and math education and cause
and effect for therapy
and as aspects such as that and then
this robot is actually coming on the
scene
so so how many people did you start with
and how has it been growing
so right now we have seven it started
with
um volunteer folks so it started with
myself and i have another founder who
is actually a person who has translated
some georgia tech he's worked with some
other georgia tech faculty so he's
basically a serial entrepreneur
and then my grad student who's now
she's now my postdoc but she graduated
so that was the device was her
thesis and
that was basically who we started with
and so now we have
seven employees so we have a ceo we have
a full-time program a full-time graphics
person
so we have kind of the team that makes
it move forward
without me
i could get back to more research
although i'm so it's like i'm still
actively there because like one of the
things we're doing is um
so the whole interface which was there
was this robot that was part of this
that kind of somehow got disappeared so
now we're we're actually maturing that
um to translate it
um but again talking to the target it
has a different focus than what i
originally
anticipated but that's okay
is it something you can talk about or is
this still like
um so it's a it's a robot coach that's
it's a robot coach and would you do
another startup or
yes i would um i definitely would i
think
so one of the things that it's done um
even for my students is that they look
at their research differently
um so they're in fact sometimes i have
to scale them back it's like okay
no more let's write this up so you can
graduate
but my students are actually when they
look at their research now and where
they're doing their subject trials
they're actually looking at it for
societal value
as well as you know this is a good
chapter in my thesis
um so it's starting to change how they
look at things as well how they look at
research
which i think is is fabulous because
that means you know when they
finish and they graduate they'll start
thinking about
oh i'm designing this new gadget i'm not
going to keep it in the lab i'm actually
going to
make it come out and have it be of use
to someone else besides
myself and you know my team so it's
that's nice i i really like that again i
have the scale of back suppose like no
no
no you know okay put that underneath
let's work on
this part and you know that will be good
product but you know let's not push that
right now
and is that something that you're able
to convey to your other students who
aren't necessarily working on this
project
like trying to make that work better yes
so
um
yes so um so i have one student so again
i've continued on
some of the more exploration so i have
one student who's working on
human robot trust for emergency
evacuations
so definitely relevant and the way
kind of starting is is like okay when he
started before
for i corpses like okay this is what i
think emerging evacuation is but
you know after that i was like he now
he's one he's gone to talk to
the georgia national you know rescue
agencies he's gone to talk to the
georgia tech
police he's he's actually been gone now
to talk
to the the target to say you know does
this make sense you know
how should i be thinking about that
whereas before it was you know oh
this makes a good and he's got even
before that i mean he's gotten a ton of
papers
so it's good stuff but now he's really
thinking about you know how do you make
it relevant um
so that's one example uh the other
student i have who's doing underwater
he's doing underwater human robot
interaction with the goal of helping
underwater divers say who are doing
scavenging scientists who are doing
things like at the coral reef
how do you design a robot that can
assist them
and so he's actually gone to divers
and started to communicate with them so
yeah it's creep it's creeping in and who
are some of your
phd students or docs have gone on to
other things
so um my i should
i have one that i shared um so siku remy
who's faculty at clemson
um he's doing basically crowd based
robotics
for education i have
another student douglas brooks who's at
sweary
he can't necessarily talk about all the
stuff he does but it's in robotics
i have another student who's at um
lonnie parker who's at newport so he's
at the
new work underwater
naval underwater naval something
something it's a newport rhode island
and so he's doing things in control
and some aspects in underwater concepts
trying to get more into underwater i
have another student who was at nasa
um brian smith he's the one that was
shared um and then he recently
and don't quote me because i don't
remember he recently left
i don't know where he went i don't
remember where he went but he
left maybe a year ago yeah maybe about a
year ago um
stephen williams who is at a startup
robotics startup either in boston or
pittsburgh
don't remember what the company's called
um
i think those are i know i'm gonna if i
forget anyone they're gonna kill me
and then hey won park who's actually my
post-doc but she's also
um co-founder of zyrobotics um
and she is she's actually interested in
academia but she's torn
she's like i'm going to go into academia
because i think it's just a fabulous job
but then she's like but i have xy
robotics so
she's a little bit torn but we're trying
to push her out of the nest
um yeah right and who are some other
people you've collaborated with
their faculty or their biopsies um so
charlie camp who's at georgia tech
um collaborated with magnus evgersten
who's control person another faculty is
patricia vela
he's a controls manipulator guy
so and he's heavy into vision so
collaborating with
him on um looking at metrics
for kids and how do you extract that
with standard cameras and not to connect
so we're so reliant now on connect but
you know
it's not the answer to all you know
there are still cameras
we were using cameras before connect
there's some value there
um so his domain is in in the camera
space stereo cameras things like that
um other people i've collaborated with
more on students frank dillard
who's a slam guy um so
he's a hardcore slam vision person he
did gt slam so that's like the big thing
now
um is frank neller outside i've
collaborate of course with my previous
advisor george becky
didst in coloration nasa folks i
collaborated at the beginning
issa and larry and he said issa
adrian stoica is another one who's a
neuromorphic robotics
yeah which is yeah he does some neural
stuff
in robotics and he does things like bci
and those kind of hybrids of stuff
um trying to think who else
maybe that's and then a bunch of
scientists but
yeah i think those are the robotics
folks and your grants have
come primarily from what sources um
prime
well big one right now is nsf national
science foundation
um some i would say surrogate nih
so um these are we've gotten some money
from
foundations that are funded through nih
so not directly through nih but
foundation funds grants um so that's for
really the studies so not necessarily
development but for some of the studies
and the assessment in that part
um yeah that's primarily nsf
and then these these foundation grants
then
when you were in now so that was great
that was nasa yeah that was nasa and
even the first couple of years that was
that was nasa funded so that was one of
their large grants
which you can get a nasa grant it's
quite nice
it's yeah it's like two nsf grants
and maybe you could tell a little bit
about your involvement in the ieee
robotics and automation society or
within the hri
community okay so in terms of
so what i would call public service um
in service
um so primarily for ieee
it's been an associate editor of x
so for example i'm the an ieee smc
they have a human they call it human
automation but i'm the
human robot person so anytime the papers
come
i have to find the reviewers for
anything hri that comes to
the smc journal um and then for raw's
the one that's coming up i'm running our
first ever phd form forum
so we'll have a phd forum at the
conference this year
which will be good and that's because
i've ran forms at triple a i
focus on robotics i've ran the phd forms
at
actually triple ai for two years yeah
triple ai for two years
um and then i'm running the phd i'm in
the phd forums the phd forum for
craw which is focused on females so
getting more females interested
so i'm co-chair of that as well so
education
is really really the name of the game
other things in ieee i've i've organized
some of the tutorials tutorial chair
um you know if i have to look at my cv
like over the years
and they've been in different so it's
not just raws it's been
um so there's raws and smc
so i think both of my homes
bras more so but smc as well
so smc has a number of roboticses
so this is before hri so what happened
is when hri was in this great area
i triple raz was like what is this hri
stuff
um and this is before the hri conference
and so you would publish in things like
roman which was a big venue or smc
or like biorob and things like that so
um
you kind of had the raw's family but
then you had to find something else
to get now we have hri so it's good but
before so you still have that little bit
of a family
um so other servers besides the social
editors
organizing tutorials um
yeah um yeah
it's a bunch of different things so you
mentioned one of those was trying to get
more women and as phds
yes what's been your experience as a
woman in robotics and
how do you see that growing uh um
so um i will say in robotics
it's there are more women
in robotics and academia
than there is in because my my home
school is
is engineering controls so there's a big
difference there
um but if i look at that there's still
not enough
um and and it's because i can if i can
count pretty much and know all the
female roboticists that are
you know in tenure track then that's
we don't have enough because i can say
oh yeah
and you know after a couple of hands i'm
done but i know
all of them not enough um and so
it doesn't make sense because if you
look at biomedical engineering
they are right now about half like in
terms of who's coming in
and this is even in grad it's about half
and half and so there's this whole thing
well
you know it's robotics it's like you
know navigation and localization and
controls
you know this is not interesting where
it's being me
it's the social value but out of
anything robotics is really
the i mean that is the social value of
anything um
and so there's there's a disconnect
there's
there has to be a disconnect because if
i look at the students that are in my
class
they're doing robotics if i look at the
bme folks
you know what are they i mean half of
the the females are doing something in
you know you know i want to design
something that can be injected into
and it's roving or i'm like that's
that's robotics no no
no it's medical it's like no so there's
a disconnect about
the message we're saying and giving um
and so i think it's like robotics of
anything has societal benefit
and everyone i mean you can go out and
say okay what is a robot to you well
like a robot x
so everyone understands that so why is
there a disconnect if i look at the
people who are creating this
and yet you know what is the
expectations and so i think there's a
disconnect
um and the reason is is because they've
done studies for this they've shown that
and even as i learned this from the
disability community if you have
um one type of viewpoint looking at the
same thing
you're gonna get the same answer which
also means you're going to exclude
everyone else that is going to be part
of that and so you really need the
different
viewpoints in order to come up with a
solution that is really universal
and so the reason why it's not just to
have it always say
it's not just because we need more women
that's not the point the point is is
that
you need a representation that
reflects the society period if you're
creating technology for society
you should create technology by folks
that
reflect society so if there were no
women in society then
i would not argue for having women in
robotics but the fact is
is you know nature kind of gives us
divide as you know 5149 or some kind of
thing
so it should at least reflect close to
that
so that's really why getting more
females and it's just getting that
different perspective
and they've shown this in the medical
world how they had technologists
and the things that came out when they
started introducing females you're like
oh
wow it's actually better yeah even
though they may have
said oh you need this for this it was
like oh but you know what everyone
really wants that
you know disabilities you know curbs on
the sidewalks
everyone uses you taking your grocery
cart or your suitcase
well guess what it really wasn't
designed for typical it was designed
because people had wheelchairs
it was like how do i get from this curb
across the street
but yet everyone is just like oh yeah
this makes it this makes perfect sense
it's the same thing so how do we get
more women
i think in something like this
giving the message that the robotics
is really about society it is creating
it's not just about
you know the best slam algorithm
although that's important it's not about
you know the best
vision algorithm that can to detect
deformation that's important
but it's also about creating robots that
can be used to
you know help the elderly or that can be
used in education
or that can be used in you know the
surgical operation room
um which it exists but really getting
that message out
that yeah it's a good thing and you do
need creative thinking and you do need
designers and you do need programmers
and you do need engineers
to make it happen diversity issues more
generally
so not just about women
so if you look at just diversity in
general
so robotics is part of the larger
problem of
stem engineering which by default is
it just we have a hard time um and
it's not just about um it's diversity
it's diversity on gender it's diversity
on minorities it's also diversity in
terms of domestic versus international
so it's just it is a problem kind of
in the u.s definitely and so
i think that message of societal value
addresses a lot of those issues i think
the concept of it's not just engineering
it's not just about equations although
you know that's that's
that's part of it um but it's it's about
making an impact and making a change and
i think that message
will affect i mean and they've shown
studies so for example
um hispanic students typically have a
very strong
family culture value you know talk about
how robotics and engineering
can address these things in fact they
have some programs that you know
engineering for native american
communities
you know how understanding engineering
can help your community
um but it's usually you know one or two
people that gave me this message and
they've shown
you know changes but it's just one or
two people and i think as
a as a society we need everyone giving
that message and not just you know me
it's like oh but it's because you you
just want people that look like you no i
think
everyone has to be part of that equation
because i don't think we can keep going
like we're going
and come up with beautiful technology
until there's more diversity of thought
and it really is
um so it used to be i was like yes no
not enough women it's not enough
minorities
it's about the diversity of thought and
and i will tell you if i'm in a room
full of females you still need diversity
of thought
period it's just you shouldn't have a
majority of one
coming up with solutions that are going
to affect the entire world
so it really is if i have a bunch of
folks that you know
all are making over a hundred thousand
dollars
you're gonna have a thought that's based
on that and then you're gonna have these
very expensive systems that nobody can
afford
so it's really about the diversity of
god and making sure that that is always
the message
and you have good societal benefit when
you do that
so i'm sorry i got on my high horse
i wonder i mean do you think that
they're also kind of institutions i mean
there's a perception problem of robotics
but there's also kind of potentially
institutional issues of
allowing that diversity to express
itself so in terms of
you know what kind of work might be
valued or you know that kind of thing is
a systemic problem um i mean there's
been like recently with the tech
startups and
you know there's this big whole you know
here are the numbers and like oh my gosh
this is really bad
um and then you have people going yeah
but you know the pipeline's broken but
not even that is like when you enter the
pipeline then it's just like why am i
here
this is horrible why do i have to fight
when i go to work i'll do something else
and make more money
um so it is a problem um
i think what's nice now which i hadn't
seen in the past
is that people are now open to the
conversation it used to be
you know just like oh people back door
rooms but now people are
open to the conversation at least which
is that's a difference that is a
difference and
and it's not a you know i grew up when
they you know we're talking about
affirmative action
you know and then it was just like okay
we're going to force it you know and so
it was like
yeah and then as soon as that was like
okay but now it's like
there's no forcing function there's no
well you have to have you know x
percentage is people are saying
hey we got a problem and that
conversation i
i really expect to see change i will not
like you know the past where
it was forced i think because people who
are in leadership positions
are actually saying this is a problem
and i am not female and i'm not minority
and i'm saying is a problem i think it
changes the conversation
definitely and what's your advice to
young people who might be interested in
the career of robotics
so if you're interested in robotics
this is the time and this is the place
and so imagine if you were
at the place where you could have been
employee number one
at google our employee number one at
microsoft or employee number one at
apple
that's where we are now with robotics
we're at the employee number
you know one through a hundred and so
robotics i think right now
is going to be you know it's gonna take
off i think we're right before that
little elbow
where you know in 15 years you know
people are like now cell phones i mean
if you don't have a cell phone it's like
something wrong you lose it you know i
think it's going to be that kind of
thing where
people are like oh where's your robot x
you don't have a robot x
why not i think that's where we are um
in the next and it's not like 50 years i
think it's in the next you know 15 years
now it may not be you know my robot made
it might be my
robot car that only gets cut on during
rush hour
but everyone has a robot car during rush
hour so now it's no longer rush hour
you know it'll be things like that where
you're not even going to think that this
was novel
and then our kids are going to grow up
and be like
you didn't have cell phones you had to
use a pay phone
with money i mean they're going to be
like you didn't have a robot
so i think that's where we are so it's a
really good time to be
in robotics to be part of the inventors
of this new world
great is there anything that we missed
that you want to talk about
i'm sure you have so much from all of us
so yeah put it into a vault and open it
up
i see all these predictions that are
either right
we can come back to them let's see let's
see everybody gets that question
that would be interesting to see which
ones are come true and which ones don't
thank you very much oh no that was fun