uh so where were you born and
your early education okay so i was born
in uh
in in india in a town called patna which
is in eastern india
and i spent most of my life in central
india
and then in in new delhi and i went to
school
uh in in central india and then in new
delhi and then i
i did my bachelor's degree at the indian
institute of technology in kanpur
which is northeastern india and at 21 i
decided
to leave india and come to the united
states for graduate education
and i did my doctoral degree at the ohio
state university where i finished in
1987.
what was your dissertation research on i
worked on trying to determine how to get
legged vehicles to walk and i spent
quite a bit of time studying goats
horses insects and then trying to
determine what kinds of gates they
employed
and how to take those gates and
translate them to robotic walking
vehicles and at ohio state we had a big
project where
we we built we a large group of people
built
a large walking vehicle which uh
weighed about 3 500
pounds and could carry about 500 pounds
of payload
and one of the things i tried to
determine was
the exact sequence that the legs should
employ in order to walk in a stable
fashion
and the other interesting question we
had to answer is
how to get the load of the vehicle
supported by six legs
in a car that's done passively you have
four wheels that support the work of
the load of a car but if you look at a
at a horse for example it has four legs
it has the option to shift its weight uh
it also has the option to
uh to take the traction forces and
distribute it in an uneven way
across its legs so this vehicle had to
do the same kind of reasoning on the fly
and that's what i worked on what was
that called that robot
so it was called the adaptive suspension
vehicle it was built in the 1980s
and and i believe it's in a museum
somewhere in columbus ohio now
but it was quite a monster
social snowballing my advisor was
uh ken waldron ken was a professor
first at houston university of houston
then at ohio state and then he moved to
stanford
and now he's at the university of sydney
in australia
so were there other people who worked on
the project with you yeah it was a huge
project it was a five million dollar
project and there were lots of people um
working on it um computer scientists
electrical engineers and mechanical
engineers
yeah and how did you just to go a little
way back how did you decide to
come to the us uh
well i it was it was funny i don't think
i had
a you know if i if i compare it to kids
these days they seem to have a five-year
plan a ten-year plan a fifth
i mean for me everything was you know
just reacting to the things that i saw
and felt
um it became clear that uh the kinds of
opportunities that were available after
an undergraduate degree in india at that
time
were uninteresting and so that's how i
decided i needed to do graduate school
and then picking an area was also
again there were some areas that were
interesting some that were not
i thought robotics had the potential of
turning out to be something
quite new back then it was not an
academic discipline
there were robots being used in industry
so when i started
there were lots of interesting problems
one could try to solve
if you look at it if you looked at a
robot as
an artificial but
smart system the human-like system
there were no such systems at that time
so i felt like there were just lots of
opportunities and i wanted to work in
this area
of course i was a mechanical engineer
and
as a mechanical engineer the kinds of
things that i was trained to think about
at that time at least were very
different
and so i thought uh walking was
something that was very mechanical in
nature and i thought i should start with
that
what was the first how did you become
acquainted with robotics
in the first place could you not rub the
wire on picking up the
friction friction from the wire okay
how did i started how did you become
familiar with robotics in the first
place
oh i don't know r2d2 was my first robot
i mean that was
uh that was the starting point and uh i
don't know i remember
vaguely a satellite broadcast of a
conference in the u.s that i just
happened to listen to and i said
you know this is something that i should
think about more seriously
what was your undergraduate degree in
mechanical engineering i was trained as
a mechanical engineer
yes and were you interested in walking
systems at that point no
no it was applied to a whole bunch of
schools
i remember looking at options looking at
cornell
looking at ohio state at cornell i would
be doing
turbulent turbulence fluid mechanics
turbulence
at ohio state i would be working on
things connected to robotics and i
decided to go to ohio state
and do you remember some of the people
who were so you mentioned you worked
with ken waldron you mentioned that
there were lots of people on this
um is it asb project so
who were some of the other uh
influential people who were part of
that project or some of the important
people
working on so um
so there were obviously lots of friends
lots of colleagues
i cannot say that i drew a lot of
inspiration from them
i think one other mentor i had was
another australian by the name ken hunt
who was no longer with us but i
ended up doing my masters degree with
him and so he taught me
a lot of very classical things and in
kinematics and geometry uh
but looking at it from from very modern
perspective
and i think he's the first person who
sort of taught me to think
scientifically and
and you know how to do rigorous
analysis and research so i think i owe a
lot to him i think if it
you know my plans to continue with a phd
at ohio state
that may have been influenced by by him
so i think he's the other person i would
single out there at a higher state
i also had a very good teacher gary
kinzell who was still at a higher state
so he's someone else who influenced me
at that time
and so were there other projects that
you worked on during your phd
uh they all had to do either with
locomotion systems
and robotics or kinematics again
kinematics if you don't know is the
science of motion so geometry is the
science of
shapes forms well when shapes and forms
move you
that's called kinematics and
so there's a lot of interesting things
that that emerge as a result of the work
in kinematics so for instance
you know surprising result is no matter
what algebraic curve you can draw on a
piece of paper
you can always synthesize a mechanical
device
that can trace that curve right for a
circle it's obvious for a straight line
actually straight line not so obvious so
think about a mechanical linkage
that you can design with pin joints
and make that mechanical linkage trace a
straight line that's a little tricky
it turns out you can do it but you can
also do all kinds of complicated things
um not sure how i got sidetracked into
this but
so the projects i worked on were mostly
in the area of kinematics and then also
in robotics
and so when you finished your phd
how did you decide to go on after that
so after my phd let's see so i knew i
wanted to do
research and
there were a few opportunities in
industry that excited me and
pretty soon i came to the conclusion i
wanted to be in academia
and i looked around for programs in
robotics and there wasn't a whole lot
back then
uh in this area and uh
so i actually you know fell in love with
penn
um uh so at that point uh
uh you know penn had a very influential
roboticist
richard paul um who actually wrote the
first book in robotics
um actually i should say in my second
year
here peter corp was here working with
lou paul
richard paul is called loophole
there was also another fairly well-known
kinematician by the name burton paul
i remember joking that pen is the only
place with two
paws with the first names that look like
their last name so the first name
they have two names that are both first
names uh rich paul and burton paul
and then also there was another person
here at that time although i didn't know
her until i joined
rushna baichi and she turned out to be
quite an influential person
in terms of helping me think through
what the interesting problems are
what kinds of research problems to
attack and so she was also here at that
time
so i like pan a lot and also
philadelphia is a great place to be so i
like that so it was a combination of
those things that attracted me to penn
what year was in 1987.
and you mentioned that there were very
before we go on to
mention that there were a few
opportunities in industry but they
weren't necessarily very exciting for
you but what were some of the industry
opportunities that existed at the time
uh so uh when i
joined academia this was a time
so robotics promised
had a lot of promise so a lot of
industry started investing in robotics
a research lab set up at that time
but the way they were going about
installing robots was turned out to be
the wrong thing so there was a boom year
the boom years of robotics maybe the
early 80s the late 70s and then there
was a bust
and unfortunately when i was coming out
it was right around
the bus times um and um
and so the opportunities that were there
were not really mainstream robotics
opportunities some of them were in the
defense and the space industry and so
because i was not a u.s citizen
that posed a lot of problems
so i had opportunities at the ai lab in
in schenectady in general electric ai
lab
um i was
looking at a t i was looking at jpl and
somehow none of these opportunities
were attractive and i elected not to
pursue them
but then when i went to academia or when
i went on interviews i found there were
many universities who were really
interested
in in someone like me and and there were
a lot of opportunities
and i knew at some point or the other i
wanted to come back to academia
to work with students to mentor them to
train them
and i said well why not start with this
what did you think was not uh was the
thing that made
the robotics industry in the early 80s
not work out
well i think uh
most of the american companies were
thinking of robots as a way of replacing
human workers
um they had these visions of a lights
out factory where robots would just
produce things and it turned out that
they grossly underestimated the
difficulty in actually setting up
assembly lines setting up production
lines
and they also did not pay careful
attention to the role of the human
worker
um so for instance if you looked at how
japanese did it i think they paid a lot
more attention
attention to how the quality of the
products could be improved
how space could be better utilized and
they spend less
attention on how people could be
replaced on robots
so the solutions that they came up with
were more holistic
and to this day i think japan has had a
better way of
looking at robotics in manufacturing
settings in the factory
than the us has
so i because of that i think industry
started getting disenchanted with
robotics
and i think some of that spread to the
federal funding agencies
so pretty soon you couldn't write
proposals with the word robots in it
so the national science foundation
obviously
was thinking beyond that and was
thinking
like most academics were nsf had a
longer vision but department of defense
was not particularly interested
neither was industry so those were not
good times
and so for for how long was the
department of defense not interested
because
now it's a very different um
playing field right no i think i think
not just the department of defense i
think
um if you were a professor
from you know 1987 to 1995
uh you struggled a lot i remember three
or four years down in
you know when i was when i was an
assistant professor
thinking that maybe this is it's time to
pack it in and try to look for something
else
it was very hard to get funding and if
you don't have funding you don't have
students if you don't have students you
can't write papers
and it was tough going at first but
you know we came out of the recession
then the high interest rate era
and i think companies started investing
in robotics again
the big auto manufacturers went back
into robotics
and uh you know i hate to say say this
anytime we
we fight wars uh we look for new
technology
and indirectly disciplines like robotics
benefit
um so i think that that's you know that
was part of it
so when you uh first came to penn the
grass lab was already
a layout and what was the program like
as far as
education for students and robotics well
when i first came to japan grass lab was
mostly a lab in the computer science
department
i was a mechanical engineer i knew very
little about computer science back then
although i was interested in it
so uh and you know rojna baichi was a
per you know
was the individual kind of make me feel
at home
in a mechanic in a computer science
setting um
but it took a while for us for me to
find my way in fact the lab was actually
extraordinarily small it was in a
basement and
more building and actually she helped
create this much bigger enterprise which
was across the street
uh in 3401 in the 90s and then
subsequently it moved here
where we were sitting so
i would say back then the the lab was
fairly one dimensional in terms of the
kinds of problems it attacked was very
computer science and information science
centric
which was which was good because for me
that was the one
way of thinking that i had not gotten
used to it gave me lots of ideas
i think it it taught me that
you could really think about the problem
of
you know so if i just back off you know
one big challenge you have with robots
operating
uh in in the real world is that they
have to reason about the real world and
there's lots of mechanics in the real
world
they have to interact with the real
world so anytime i pick up an object
it's a problem in mechanics there's lots
of mechanical engineering in there
and so unless you understand the
mechanics unless you understand the
interactions that occur
it's very hard to just think about
writing for example control code
or even code for perception and
all that is very fundamental to getting
robots to work
so um it really made me
sort of think harder about these
problems and so to
this day i think a lot of the things
that my students do
is largely about creating software
systems
but there's mechanics inside
all the software models um
and i think a lot a lot of that really
came about because of my
exposure to fellow computer scientists
in the graph
grass flood recovery and so in those
early years you mentioned that rogenda
made you feel comfortable as a
mechanical engineer in the computer
science
or computer science lab um how did those
interactions happen well so
so rojna was you know interested in
problems and perception
problems in artificial intelligence
and how you could actually solve some of
those problems using robots so
very early on she had this this great
idea
which is now called active perception
this idea that
um in order to perceive the world you
need to move
um and so when you need to move there's
motion involved
and so there's mechanics in there right
she was also interested in how you might
explore environments so if you pick up
objects and you heft them you you wave
them around
you learn a little bit about the objects
so again this is perception but
the underlying problems are really
mechanics oriented
and so she was interested in how robots
can cooperate
and so early in my career at penn we
started looking at the problem actually
with her
and how do you get robots to cooperate
to pick up for example pieces of
furniture and carry them
well unless you really understand the
mechanics unless you understand the
control
of the robots and the interactions with
the objects it's very hard to solve
these problems
so at a high level she was interested in
exactly the same problem that i was
interested in
except her methodologies were very
different she was trained as a computer
scientist
she was an image understanding person
she was an ai person
and here i was coming at it more from
the dynamics from the control side of
things
so that's an example of the synergy and
you know
we were often talking about the exact
same thing but in different languages
we learned each other's language and
that helped
what was the first big project you
undertook once you got to
upon so i think uh there were a lot of
projects we undertook but i think one
big achievement in the late 80s early
90s
was exactly this thing i was telling you
about so we got
robots to actually cooperate to carry
objects
um so this may sound uh quite trivial
but if you just think about the
the problem that these robots have to
solve
you know each one has let's say an arm
and
it knows about its own arm's position
how its own arm is moving
but it doesn't know what the other arm
is doing
and so these robots have to sense each
other
through forces and they have to
coordinate motions
again what these robots know is the
overall task which is to pick up this
object and move it
so one very cool problem we solved is
how do you get
two robots to manipulate objects such as
balls and so i don't have a ball in my
hands but you can imagine
if i want to manipulate a ball
i not only have to move my arms but i
also have
to let the ball roll along my palms
and so you have to model this and this
is quite
intricate the model is complex and then
to try to figure out how you can get the
robot to do what you want it to do
using information that the robots can
sense
you know positions uh forces at the at
the
palms perhaps position of the ball
as it contacts the palm this is very
tricky
and so that was a big accomplishment in
the early 90s
and who funded this research uh so this
research was funded in part by
a darpa project that that
roshnow is the pi on and by that time
i'd already gotten some funding from the
national science foundation
um actually in 91 that was sort of a
turning point where i decided yes i'm
going to stay in academia
where uh i was fortunate to win
what is now called actually i don't know
what it's called now but it was called
the presidential young investigator
award
um in 91 and so that gave me enough
funding to do the kinds of things i was
interested in
and that was kind of a turning point um
but it was funded income mostly by nsf
and a little bit by darpa
to answer your question so what was the
next set of projects you worked on
so i did a lot of things with again
coordinating arms coordinating
fingers working in the grasp lab i had
to think about how robots grasp objects
no
just joking but we did again the
problems are very
similar i think one
project that received a lot of notoriety
is we were able to actually
going back to my roots where we worked
on walking vehicles
we developed initial prototypes of a
walking chair for disabled people
so people with disabilities you know if
you want to walk around
you're constrained by human-made
environments
and you really can't do things like take
a walk in the park
the park is not doesn't have a paved
surface and this is something we really
worked hard on
a group of very smart students who
equipped
conventional chairs with leg-like
crutches and that would allow them to
get over obstacles
and this is the smart chair project no
this is called i think it's called the
walking chair
okay were there attempts to
commercialize this
uh yes so we talked to actually there
are some companies that came to us i
remember johnson and johnson came and
spent a day here
this was shortly before they decided
that they would
um put their eggs in the dean cayman
basket
uh you know the i forget the name of the
the you know the segway-like robot that
he developed
anyway so so but then they decided that
was a safer bet
i think the world was not ready for uh
the risks associated with embedded
processors and devices that you have to
rely on
so and wheelchair companies
were quite risk allergic they i mean
partially because they're regulated
in a strange way because of the
insurance industry
but partly because it's not an industry
that even today
you don't see a lot of innovation i mean
wheelchairs are roughly where they were
after world war
ii um and so but
but that so there were attempts to
commercialize it but
neither of them none of these attempts
really went very far
and so after the walking chair what
other
kinds of projects were you used to so um
after working on these walking chairs
so again the common theme in all of
these projects is
that you have robots or subsystems
of robots that need to cooperate so if
you think about legs
the legs cooperate in order to walk the
vehicle forward if you think think about
grasping you have the fingers that kind
of cooperate to manipulate the object or
arms that need to cooperate to pick up
things
and so in the 90s
mobile robots became very very popular
and so we started
thinking about ways that mobile robots
could collaborate
on tasks so we developed the first
mobile manipulators arms mounted
on on mobile robots and we
showed how they could cooperate
we also looked at how
a team of mobile robots could solve
problems that individual robots could
not solve
so for instance problems in
cooperatively exploring environments
cooperatively mapping environments and
to to this day we have unsolved problems
that we're still attacking
uh with those kinds of robots
so that was in the late 90s and the
early
21st century then most recently we've
been
very interested in how we can actually
take all of this to the third dimension
so now we have teams of aerial robots
doing much the same things that ground
robots
were doing and of course aerial robots
are really game changers because they
can do things from the top
so ground robots are either bolted to
the floor or they're moving around on
mobile bases and
aerial robots you can do lots of things
that you cannot do with ground robots
so we're interested in how you can have
aerial robots
cooperatively explore complex
environments how they can collaborate on
picking up objects and manipulating them
how they can do assembly and a large
part of my lab right now works on these
kinds of problems
what are some of the principles and i
guess findings that you based
these robot collaboration on throughout
the years so what
are you asking a visit are you asking
there's a unifying theme
through all of it no no so i'm wondering
of course your way of looking at what
collaboration among robots means and the
different
ways that you've managed to have it
implemented have probably changed
through the years so i was wondering if
you could tell us a little bit more
about the
kind of science behind the
movement yeah so what so i mean
cooperation means lots of
interesting things to um different
interesting people
and uh the the
the one thing that actually the common
thread between all the things that we do
mostly
has to really do this underlying the
underlying physical models that govern
cooperation
so especially when you when you
collaboratively pick up objects you
collaboratively assemble things
but i think more importantly uh the the
question
in in academia that you want to ask is
in addition to is this problem
interesting or not does it kind of lend
itself to academic research
does it lend itself to training of
doctoral students and that's something
that
um you know penn has a tradition of you
know we're committed to this and i
personally am very committed to that so
i think that that is one thing that you
have to look at
so you have to take the overall problem
dissect it into smaller problems
and then go into attack the smaller
problems that
lend themselves to writing of doctoral
thesis
and so what are some of the approaches
that you use to
develop collaboration among the robots
so
uh yeah so you i don't know that i could
i could uh talk about a unified way of
of doing this but let me
at a higher level let me try to
articulate some of the design
philosophies if you will so if you look
at nature
where you have groups in nature that
collaborate to do tasks that individuals
cannot
you'll find several common features here
so
one is nature
has solutions in which individuals
accomplish
their little piece in a completely
decentralized way
so again if you and i pick up that table
and walk out with it i'm not going to be
telling you what to do
neither are you going to tell me what to
do i do my own thing you do your own
thing
but if we are truly cooperative the
thing that we want to do gets
accomplished
it's even more obvious when you look at
for example ants so we spent a lot of
time studying ants
and now ants cooperatively carry objects
that are many many times
their size and
again if you look at the the actual data
coming from ants
it's very clear that every ant is
actually doing her own little thing
but the only little thing that that she
does is so carefully designed that if
everybody does the same thing
right the task gets accomplished and so
one of the goals in cooperation is to
find out
how to decompose a big task into these
little subtasks
the other common thing about these
solutions in nature and the solutions we
want to implement in robots
is that each individual operates on
local information
so again if you and i collaborate i
cannot possibly know all the things that
you know
and you cannot possibly know all the
things that i know and
oftentimes when you're carrying large
objects
we don't even see each other in fact i
don't know what the object looks like
from your side and you don't know what
the object looks like from my side
so whatever solutions you develop has to
lend itself
to implementation using these very
modest assumptions
i know what i know you know what you
know and the question is
what do we have to communicate in order
to make sure that this task still gets
accomplished
okay and the third thing that is sort of
common to all of this is
uh what we like to call anonymity
so when we cooperate the best way
of cooperation is to assume that we're
all anonymous
in other words i make no special
assumption
about who i'm cooperating with and the
other way around
and again this is true and ants i mean
ants have very limited knowledge of who
their neighbors are
they can identify neighbors if a
neighbor is there or not but they don't
know which neighbor is there
and you can argue it's because ants are
homogeneous
but actually that's not true i mean
there's as much heterogeneity in
ants as there is in humans but actually
what
what what the end result is if you
assume homogeneity
then the kinds of solutions that work
are ones that are fairly robust
and that's something else that we try to
realize in all our
uh and all our robots
and the the the the side benefit to all
of this is
that if you assume homogeneity the
software i use for robot x can also be
used for robot
y and so this notion of anonymity helps
and you know i used to joke that when i
first started working in robotics
to do a one robot experiment that you
need one student to do a two robot
experiment you needed two students
plus a third one that kept track of how
the interactions are going
well you can do the math if you do an
end robot experiment you need kind of n
squared students and
and if if n is if you don't have that
much money you don't you can't do
n squared experiments or end robot
experiments
so and biology again breaks this it
breaks the symmetry by saying well
all you have to do is figure out what
one robot does and then just copy it for
everyone
and so that was a big paradigm shift for
us and how we thought about robot
software
and robot mechanics in the same problem
in the same in the same vein
how did you start looking at things like
ants or
biological paradigms well
um i think so this has been a theme i
think in
most robotics research if you try to
build intelligence systems
you try to look at proofs of concept
that already exists so i think you'll
find that many people actually do this
of course it's very hard for roboticists
to go into
the field and study animals
and so oftentimes this works if you can
strike up good collaborations
and one of the people i work with is
is a professor in arizona state stephen
pratt who studies
ants and end behaviors so with him
we've been looking at
some very interesting problems so one is
cooperative
pre-retrieval so ants
is a species of ants that you know when
they find
prey they take the prey back to their
nest as opposed to eating it right there
and oftentimes you know spray is pretty
big um
so he did this initial experiment with
with a piece of fig
that was about 20 times the size of an
individual and sort of
the ants sort of recruited their ants
and they carried this thing back
so we got this idea that well maybe what
we should do is to
build artificial figs so that we can
try to fix it or instrument these
artificial figs so that you can actually
study the behavior
of the individual ants and so we started
working on this
and we found that if you take a piece of
plastic and you smear fake juice on it
the ants will carry it
and then if you build the plastic to be
deformable
the ants will actually stretch it or
compress it as they move
well if you take an object that's being
carried by multiple people that actually
stretches and compresses
you get a pretty idea of good idea of
who's doing what and so that was our
first
instrument so passively by looking at
the stretching and
and compression we were able to infer
what
what ant is doing what and we're also
able to track all the ants
that was sort of our first study and
that was kind of cool um
so with him we're also learning how ants
recruit each other how they actually
teach
each other paths in a complex world
which is actually
quite controversial this idea that a
leader teaches a follower
how to go from point a to point b which
ants supposedly do so we're trying to
verify it by
by by creating little robot ants that
teach
uh real ants the wrong path and see if
they continue to follow the long path so
this
is a lot of interesting stuff you can do
if you really look at robotics and
biology
and at a high level we're both trying to
answer the same questions
and there's a lot of synergy you can
derive from each other by just sharing
results
and sharing methodologies are there
other people that you've collaborated
with over the years
uh yeah so i have a uh
i have a collaboration i have many
collaborations here at penn
uh molecular biologists and cell
biologists
so some of the behaviors employed by
groups of molecules groups of cells
again they've developed highly efficient
mechanisms
to for example sense quorum
so how do how does a group of cells
decide
that itself the population of the cell
is about a certain threshold it's time
to now
start doing something else
in bacteria there's this phenomenon
called
persistence
where they they actually are robust to
attacks from external agents like
antibiotics for instance
and so it turns out there's an
underlying behavior called the stringent
response system
that my colleague harvey rubin has told
me all about
and so we've been sort of looking at how
those kinds of
behaviors can be realized in real robot
systems
to make them more robust and make them
resistant to external threats
so there's those synergies most most
recently we're working on
micro robots that are actually powered
by bacteria
so one of the things biology has that
we've not exploited is roboticists
is this amazing set of actuators so
bacteria have these flagella that propel
them
through fairly remarkable speeds through
fluids
and so the idea is if we take these
bacteria and we attach them to a robot
and we get them to swim the way we want
well we've got a robot
a small robot that can swim the way we
want
and so we've been doing that in the lab
so there's this
there's a lot of interesting
collaborations we have right now with
biologists here
who are some of the people you've
collaborated with previously on
other projects
uh i have too many of these i look up my
list
i mean some of the ones that kind of
stick in your head as people that you've
worked with a lot or
you've had very fruitful collaborations
well yeah certainly so i think penn is a
very collaborative place a lot of
colleagues here
that we work with a group works with
one of the things that's that's nice
about pen is we're very small
so if if you're small you don't have too
many people doing the same thing
and if you don't have too many people
doing the same thing you talk to people
who do different things
and that sparks the really interesting
collaborations
so we have an extraordinary controls
group here
we have a great vision group here and so
there's a lot of interesting
collaborations there we also as i've
said
have a excellent medical school and
biologists who we collaborate with here
so i can give you names of some of these
people if if that would interest you
um okay um
yeah and also any students you've had
who've been
moved on to be a professor as well oh i
mean i have
i have lots of students um how much time
do we have
um i have to say that's the one part of
my job that i i really enjoy which is
working with doctoral students
um you know you
when you when you we work hard at
recruiting doctoral students and
i just enjoy the process because you
know you
you try to attract the top people um
and they're like um
you know uncut stones and then all you
have to do is
hone them right until the stones become
gems
and so this is so this is a this is a
part that i enjoy a lot
um i've had
uh you know close to um
i think i would say 30 phd students and
a good fraction of them are in academia
themselves
um and several postdocs to
be close to maybe 20 again many of them
are in
academia and the reason i single out the
ones that are in academia
actually haven't singled them out but i
mentioned that is because
i think you know they i think i've
transmitted
my love for sort of supervising other
students to them
and i think it's good that they're going
on doing the same thing
um so you asked who are so just
just most recently i had i had let's see
the last student to graduate was
um uh actually last week
um uh norah ayanian who's uh
who's uh she is um she's still here
she's
wrapping up a phd student a phd thesis
sorry
and she's looking at academic positions
post-doctoral
job opportunities
the one before that mahmoud salman's
soccer is a
p is a postdoc at mit um
and then uh before that spring berman
she's a postdoc at harvard
um i can go on and on i can give you all
kinds of names what about the early ones
from the 80s
so my very first phd student nathan
aldrich
was probably the smartest mechanical
designer that i ever had very creative
guy
he ended up doing a postdoc at woods
hole um
oceanographic institute um and
then he ended up establishing his own
company
called technique
so he really wanted to create new
robots build new robots and i think he
continues to do
work on novel devices
uh at this company actually he and his
brother started this company that
uh uh manufactured the high-end
uh scooters you know these this is when
when did scooters become a rage um
you know not not not the other push
scooters yeah thank you
looking um so uh they produced
what they called the rolls-royce of
scooters so this is for people like you
and me
so actually i have one in my at home so
a really nice scooter is made out of
solid stuff
not not this made in china kind of a
production model
so they made those they made electric
bikes long before electric bikes were a
big
thing now of course you go to shanghai
and
any snapshot you take will have seven or
ten electric bikes in it
so so he continues to do you know these
kinds of
things creating novel products and
bringing them to market
where is that it's based in boston and
actually i don't exactly know where but
he is in the massachusetts area
has your um throughout some of your work
have you worked up
has it gone towards particular
applications
um well i mean when you do research
obviously you want to be
aware of applications and be guided by
them but it's it's
it's a little dangerous to be obsessed
about applications so we try not to do
that
i mean ultimately the the work that you
do
even though it's an engineering thesis
has to stand on its own
so no we don't particularly think about
real applications
although i have to say most recently the
project i'm most excited about
is one that is really motivated by
applications
um so i'm sure you're all aware of the
the tragedy in fukushima
and it's ironic that
that that the tragedy happened in japan
a country which is known for its
robotics work
and uh yet there was very little that
the experts
uh could could do and there are many
reasons for that
um so one of the things we're really
interested in doing is to
bring um aerial robots
and apply them to this setting and we
also want to think about autonomy
so one of the difficulties in these
kinds of settings is you cannot
teleoperate these robots
you're not allowed to come close to the
actual reactor building
because of radiation dangers with
radiation
second even if you come reasonably close
the communications link is actually
greatly impaired because of
electromagnetic radiation
so what that really means is you want a
robot that goes autonomously
gathers data comes back to you and
reports
uh well it may not come back to you
chances are that robot is lost forever
but it has the data it gives you the
data and then it dies
right so we're trying to explore this
paradigm
uh in the setting of you know buildings
in the fukushima area we're going to
start with sendai this summer
send our robots to some of these
collapsed buildings and so here's a
project where
uh we want we want to solve this problem
we want to
attack this application area and we
think there could be obvious benefits
here
so we're doing that but in general we
don't we try not to do things like this
do you work with any japanese
collaborators yes so we're
we've just started this collaboration we
have a pilot grant from nsf to go
visit um tohuku university
in sendai and we're going to perform
some preliminary experiments this summer
um so besides your own work we
talked a little bit in the beginning
about the grasp lab and you've also
directed the lab
for an extended time and so we were
wondering if you could tell us a little
bit about
the development of the lab what it was
like when you know you got there
which mentioned a bit what it was like
when you took over the director to ship
and you know how it's developed through
the years robotics is a program
yeah sure i mean i think uh when when
rouge now was there she really had the
vision to set up the lab
she also acquired space some really good
space for us and helped nurture the lab
during its early years
and but when she left there was a big
leadership vacuum and
and that was pretty challenging to sort
of step in
and as i said you know there were mostly
computer scientists and and i was alone
non-computer scientist
yet running a lab which really was part
of the computer science department
i mean that's not to say that you know
my colleagues made me feel welcome but
but still it was a challenge
i think the one big change during my
tenure as
as as a director was to take the lab
and to bring in more participation from
other departments
we recruited some top-notch electrical
engineering professors
and so right now you look at the lab
whether you look at faculty or
students or post-docs it's roughly
one-third mechanical engineering
one-third
computer science one-third electrical
engineering and really that reflects the
true nature of the of the discipline
so i would say that it shifted the the
overall research if you looked at the
lab it moved more from the
perception-centric
um programs research programs that
rougena was
more interested in obviously she was the
person in the world
in that area to i think more
broad-based programs which brought in
control
coordination communication
design and i think that was a big
come to be the shift
i don't know so sadly
um i i think it may well have been that
uh i mean i was pretty junior at that
time but but i was i was
the next most senior person after
drizzner
and i guess it fell into my lap
do you have any favorite stories from
the
lab or its development
uh you know the the the one thing i
remember is that
um so from my really early days i
remember
that
i used to come in on sundays uh roojina
was there on sundays and
all her students were there on sunday um
and they would all have their weekly
meetings with her on sunday
and if she was there they were all there
it was just amazing and i've never
seen this culture elsewhere um
that was the one thing i could not
sustain
uh mostly you know because of me once i
had a family and so on it's hard to do
but
but that didn't happen so that was that
was
somewhat funny the other thing uh there
was actually
she had this um this this t-shirt
the sweatshirt which had uh the world
results printed on the back and uh
that's all she wanted i want results and
she would turn her back and walk away
to our students uh that was funny but uh
those those yeah
and you know i still tell my students
this so they say well can i take this
time off i said i don't care as long as
you deliver the results right
and that's what it should be about right
so
um yeah how do you see the the strengths
and aims of the robotics program at
penn relative to some of the other
robotics programs at mit very friendly
so uh yeah i mean there
i think there are many outstanding
programs i would say
we're among the top five if not the top
three um
i think uh in terms of size i think
carnegie mellon is the big outlier
they're about
i would say 10 times our size um
uh but and that's i think in terms of
um i think they have a culture of going
after big
projects like grand challenge for
example
um while we probably don't i think we
pay a lot more um we're probably a lot
more
uh academic in in nature i think
we spend a lot more time thinking about
doctoral education
not to say they don't i think that's one
big difference
you know mit is great
much of mit's program is anchored in the
artificial intelligence laboratory
it's sort of computer science and
artificial intelligence
so i think that's the difference i think
this this is sort of unique in the sense
that
it is you know common space that's
shared by
three different departments
and you know to this day you walk into
the lab and you have no idea
which space belongs to who and to what
department
you walk into the lab you'll see lots of
students and i guarantee you would not
be able to identify who's a mechanical
engineer
who's an electrical engineer who's a
computer scientist and i think that's
that's
very unique of of penn
we're also incredibly collaborative i
think it's it's uh
i'm really amazed by how students write
papers together and oftentimes the
advisors don't even know that they're
collaborating with other students and
it's great so i think that culture is is
part of
you know who we are
how do you think robotics particularly
the fields that you've been interested
in have changed through the years and
what are some of the future
challenges um
let's see so if you look at uh
cooperative robotics i think
you know one thing that has happened
over the years so so robotics
like many other sciences i think it has
been greatly influenced by
technological advances so
i think the biggest technological
advance obviously is processing
right so you know about moore's law and
all those things i mean
i remember when i was a doctoral student
when we were implementing code we
actually had to worry about the number
of ads and multiplies in our code
to make sure that we weren't overloading
the processor um
again to put things in perspective i
back then i programmed with 8086
intel processors if you don't know what
that is you have to go back from a
pentium
before that came a 486 386 286 and then
an 86 so it was that
that long ago um and uh
and uh so now you don't have to worry
about that um
in some sense i think we're spoiled by
that largest but in another sense i
think
it's allowed us to dream and you know do
things
that we're thought to be completely
infeasible back then
i think the other technological change
that has happened is i think if you look
at the
uh the price to performance ratio of
sensors
that's fallen dramatically so we now
have a lot more data than we could have
hoped for
and again that has influenced how you
think about problems
um i think the third thing that i would
i would
i would say is that you know again going
back
we just did not have a critical mass of
roboticists
creating robots now it's relatively easy
if i want to make a particular robot
with
some sort of a specification unique
specification for a particular task
it's not a big deal i can do it
or if i'm too lazy or if i don't want to
spend my energy doing it i can go buy it
that was not the case before right so
when you think about the work that we do
here
so for example one of my most successful
students nathan
michael who was who is now a research
assistant professor here
he decided that he wanted to build his
own robots
and and he took a combination of
off-the-shelf
parts and fabricated other parts and he
built
his own multi-robot system um
i mean not to take away from his uh
creativity and his
and his uh and his novel designs but
you know this was much harder to do a
while back
um so i think the these technological
changes
have influenced the way we think about
problems and the problems we think about
solving
um and so so what are some of the
kind of new problems that you can now
think about solving that you wouldn't
have thought about
right so for instance now uh you know
we're thinking about
deploying tens of robots
in in you know in a building in in
in this in this engineering complex so
for instance last year we
uh so i talked i told you about nathan
he was involved in this too
we did an experiment where we had
we told a robot to go
not just into the next building but the
building adjacent to that
into a corner of that building and to
get there and tell us what was happening
and so this robot was able to recruit
other robots
that acted as relays and they set up
their own wireless ad hoc network
and so i'm sitting here and i could
actually in principle observe what was
going on
in a corner of the town building so you
need lots of robots to do things like
this
and again oftentimes we don't attack
these kinds of problems unless we know
that these problems are doable
in the real world so that's an example
of something we would not have attempted
10 years ago
what do you think are some of the coming
challenges in robotics
i think i think one huge change i think
is our ability to really
develop three-dimensional autonomous
flying robots the uav industry is huge
mostly because of these big drone
aircrafts that
fly at really high altitudes and do bad
things that
i don't care about but i think and
they're very expensive
but i think the time has sort of come
that you can take those big objects and
scale them down to really small objects
and then make them completely autonomous
so if you do that i think the third
dimension adds so much to robotics and
if you know i if you look at the number
of aerial robot
sessions and conferences it's exploding
um i think so that that's a big change
in the next four or five years that
you'll see coming
do you what do you see is the social or
societal
role of robotics if any um
you mean what role society has to play
or the other way around you both but if
you could answer both it would be great
so i think uh the one thing so
you may or may not know about this but
there's a new robotics initiative that
we're helping
push through washington and
we hope there will be funding for all
kinds of new interesting projects
both in academia and also in industry so
this is called robotics 2.0
so as opposed to 1.0 2.0 now
acknowledges and emphasizes the role
that humans play in a robotic society or
the other way around robots play in a
human society
and so the the increasing the
realization is that no matter
what uh the the application you want
humans and robots to work
together um and i think that
is gonna you're gonna see more and more
of that already it happens
in uh for example in in the operating
theater where
surgical robots are operated by surgeons
and there's there's things happening
together
i think it happens a little bit in
factories where you have humans working
next to robots
in the kinds of missions that i was
talking about in fukushima it's
it's uh it's hard for humans to do it
alone
so they'll need robots on the other hand
robots will need to
complement humans and i think that that
is going to
you're going to see more and more of
that and
right now the only robots we have in our
homes are vacuum cleaning robots
you know partially because of economics
partially because of what society is
willing to accept
but i think you'll see a lot more of
these kinds of robots in homes
and and i think it'll bridge the gap
between humans and
and and robots and i think you'll see a
lot more of robots
everywhere um let me just uh
do you want me somebody not yeah yeah i
just wanna we can have just one
yeah and i think yeah yeah you have to
pack up stuff and
that's it it's all yeah
but our final the question that we
usually finish with
um is if could you give some advice to
young people who are interested
in robotics
how young are these people it doesn't it
can be
any any age that you think of course now
it's from pro
from k to yeah well okay so i mean
here's my
um so from the standpoint of education i
think
i often call robotics the canonical
engineering discipline
and the reason is it's it's a it's
synthetic
unlike many engineering disciplines
where you analyze things here
the whole goal of robotics is to build
things
and it forces you to learn the science
that you need
to build these things so if i were to
restructure engineering programs
i would simply have the very first
course be a robotics course
and from that build
engineering science courses that could
help students build better robots
so this is sort of a top-down way of
doing robotics
but getting off that soapbox i would
tell students that this is a good way
to learn a wide variety of techniques
that are used in engineering
well today robotics doesn't include
biology as much as it could so
bioengineering and biomedical
engineering is not
really a central part of robotics but
that's just a question of time i think
that'll
that'll also creep in likewise it may
not include chemical engineering or
material science
but i think again it's a question of
time we're going to be looking for novel
materials
and so it is really the best way to
learn about engineering
so if you're interested in creating
anything
in an engineering type setting
building physical devices robotics is
deep discipline to get interested in
i would also say that it really has a
truly transformational
ability here or potential here so you
know if you look at
um so the us is not yet doing this but
if you look at uh
for example japan korea europe
many countries in europe in a handful of
if you were to single out a handful of
technologies that they're sort of
emphasizing robotics is one of them i
think we're a little bi
behind the curve but i would tell people
this is where the action is
this is where you need to be why do you
think
i think we are a lot more
careful about adopting new
uh top-down initiatives
i think we're a lot more free-spirited
and i think that's good that's why i
think we attract the best talent
but if robotics were a social movement
then i think everybody would buy into it
in a heartbeat
but i just got off my soapbox but when i
was in my soapbox i'm preaching to you
and you're not gonna accept that right
so you gotta believe it
so i think today the kids are believing
it i mean you see
um you know we run the first lego league
competition
out of at penn and i was the head of all
judges
so i'm looking at these third graders
these fourth graders the fifth graders
and they are trying to explain to me
the basics of control as they see it in
their robots
and you know that you know we're
connecting with them indirectly so i
think this is really the discipline to
be in that sense
uh and so i think it's a question of
time before we buy into it
at the at the level of washington and
below
um and the new robotics 2.0 initiative
hopefully will
reinforce that
thank you thank you thank you so much
yes no that's great