i
uh okay so you so we want to go back to
college or we want to go back
with uh where you were born and where
you grew up i was born in montclair new
jersey and i moved
from a ver to a variety of different
towns in new jersey
and eventually my family moved to
montclair back to montclair
and i spent my formative years going to
montclair public high school
um where i learned everything i really
know i think
at least anything i know that counts
other than montclair public high school
and i was um and i was a historian maybe
or
interested in literature and i
was going to be an english major so
that was what i was never good in math
in high school never never good
uh and then
i went to i graduated from high school
during the time that the protests
against the vietnam war were raging and
that had a huge
impact on all of us uh i don't know what
i would have done about the draft i had
a very high draft number in those days
everyone was given a draft number
and if your number was low enough
and the threshold was crossed then you
would be drafted into the army and many
people
either went to another country or they
found a way to be conscientious
objectors or they went to jail or you
know
so i don't know what i would have done
exactly i was i didn't
it was a very very important experience
for us at that point to
recognize how what mistakes the country
was making
in vietnam uh i had a
my draft number was like 364 out of 365
uh 363. so it didn't uh it didn't become
an issue
um so i went to college i went to
college at yale university
i started out as an english major um
i gradually became disaffected
if you got to write about what other
people got to write it'd be okay
but you you had to write about what
other people write about what other
people write about
and so that third order removal was just
a little bit too
too hard and it
it began to it was also clear that
uh technology was moving ahead and doing
some
that was very interesting um
uh it was a time when people were
turning their backs on
the pro the agenda of logical positivism
that kind of
long ago spun its course but uh you know
i was confused
as to why wittgenstein had renounced
that
the whole idea that why language games
you know why not uh
logical positivism uh so so i moved away
from linguistics and started
taking more courses in
uh well from english to linguistics from
linguistics to
uh maybe anthropology maybe social
anthropology maybe physical anthropology
and
eventually um came to realize that uh
being in college didn't make any sense
and so i dropped out of college
and i worked for a little bit of time
and uh then came back and the time i at
that time i i
was out i had started getting very
interested in weiner's weiner uh
norbert weiner had written numbers of
popular books about technology he didn't
write just mathematical books i couldn't
read the mathematical books
but he wrote these popular books god and
golem and things like that about
cybernetics and what cyber ethics would
mean
uh and it became increasingly irritating
to me that i couldn't read these
mathematical that there was this
language i had never encountered the
notion that i couldn't there would be a
language that i couldn't read and i
i thought this is so you know don't why
would you
why would you be in school and study
something that you could study on your
own why not
use school to study something you
couldn't possibly do by yourself
so i went back to school and um i had in
mind to maybe do some kind of
try to force myself to learn mathematics
or do mathematics even though it would
be very hard
um i met when i got back i met an
engineering professor at yale his name
is narendra
kaznarendra who had a huge huge impact
on me he was
uh in this tradition of cybernetics and
he was a what's called a control
theorist by then we had stopped using
the word
cybernetics and started talking about
control theory uh
and he was very very interested in the
intersection of mathematics you know the
unreasonable effectiveness of
mathematics in the in the in the
physical
in the material world uh very
smart obviously very smart guy but a
very thoughtful guy
not your typical engineer as i thought
engineers typically
were um so i got very uh close to him
intellectually and by the time i
finished college i finished two years
later i was working almost exclusively
with him
in his lab beginning to write a few
simple papers under his
guidance i had learned enough
mathematics painfully but i
was able to do it to be able to start
writing some papers
um and then i quit and then i graduated
and i swore i'd never go back to
academia because
it was all you know all the this was at
a time when the world was changing
rapidly and we didn't know
uh it looked like the social obligations
were much stronger than the intellectual
obligations i'm a citizen of the world
so i went to become a literacy tutor in
um
in new york state uh um
in an area uh where the
there was a migrant stream there was a
fruit and vegetable
worker stream that was very
disenfranchised
and there was a there was a non-migrant
stream of of native americans people
whose families had come over and
mayflower who were
involved in dairy and beef farm labor
and they were equally disenfranchised it
became clear to me gradually
not so quickly that they needed much
more than literacy
so i began to work uh
i began to start we were very influenced
by cesar chavez and his
his work with the farm workers on the
southwest
um we thought well there should be a
farm labor organization in the northeast
and so
a group of friends and i and together
with some of the farm
workers began to build a farm labor
organization
that was very exciting um but it didn't
work very well i wasn't i'm not a very
good organizer
uh i got very very tired
we weren't having great success uh
and you all this time i've been going
back to work with narendra i
would spend uh oh maybe every two months
i'd come back and
work with him and then every month i
would come back and work with him and
then every other week i was coming back
to work with him
you know at some point he said well who
are you fooling here why don't you just
come on back and be a graduate student
so that was a very you know at that
point that was uh 1979
i guess 79. yeah i stopped being
a public citizen and i became a narrow
you know a monk an academic i mean i
stopped
thinking that i was not going to be an
academic um
and then from that point on i had a very
straightforward
up until then i had a very
non-straightforward entry into academia
but
from that point on i had a very you know
traditional uh
experience in academia i had the good
fortune of an extraordinarily
attentive and thoughtful mentor
um uh
so in some sense anything i know
anything i know about the world i
learned in montclair public high school
anything i know about
my field i probably learned from this
guy from my mentor from
narendra and everything else is kind of
a detail but
important details but he really really
had a huge impact on me
so you're studying control theory yes he
was a control theorist
he was he was a control theorist in in
what then became the elector eventually
became the electrical engineering
department
uh and the
role of control theory as i guess you
guys already know is to try to
reason formally about the way in which
dynamical systems can be affected by
external influences so there's a world
of dynamical systems that is much older
the world of dynamical systems got
started
essentially with juan poincare in the
late in the turn of the
you know late 19th century um
and and it was the beginning of a new
branch of mathematics that gave rise to
what eventually became combinatorial
topology or algebra
analysis c2 it was then called and it
became uh
algebraic topology as it's now known but
it was then combinatorial topology so it
was a way of
um trying to understand how what's the
geometry of change
or what's the geometry of evolution
there's a geometry there but it's not a
it's not a spatial geometry it's a
spatial temporal geometry and
poincare got that off the ground um
the first control paper was written by
maxwell and james clark maxwell in 18
i don't know 670 something i forgot what
it was now
you guys probably know these papers
maybe you know
um and he looked at windmills
he wrote down a little model of a
windmill they looked like they
the people had been building windmills
for many many many years but the
urgency to understand so so if the
wind if the wind didn't blow fast enough
then the windmill would turn too slowly
and the emperor's corn wouldn't be
ground
at the right granularity and if the wind
blew too quickly then the windmill would
turn too quickly right and so
the emperor's going to be ground too
finely and so that you know and so the
people would lose their heads and so
they people began to build
governors as they were called to adjust
the sales of the windmill
furl or run for all the sales as a
function of the speed
there was a very long tradition of this
that had only gradually
that only gradually became understood
people built
uh floating clock valves you probably
are familiar with these olds
going back to historic to antique time
of antiquities
um but maxwell was the first one to
recognize that
um if you didn't get these feedback
systems right then they would hunt or
they would
go unstable or they would shake
themselves into pieces and if you were a
really master crafts person and had
great insight then you would
get exactly the right masses and exactly
the right
lengths and you would build them so that
they wouldn't shake themselves to pieces
um maxwell wrote the first analysis of
what
why something would shake itself to
pieces and it turned out that
it had everything to do with the
resonance phenomenon that's very
familiar to kids who blow across a
bottle
any anything that has mass and
springiness
to it and some damping is going to have
this trade-off between
um how how how shaky it is
versus how slow and molasses like it is
you'd like it not to be molasses-like
because you'd like it to respond quickly
but
if you allow the thing to respond too
quickly then it's going to start getting
the shanks
and so maxwell developed uh realized
that you could
to first order you could understand this
just by writing down
a simple newtonian spring mass
damper equation and looking at the
interplay between the mass parameter and
the spring parameter
and in some sense that was the first
that was the beginning of um
control theory and then you know the
control fears got
a huge boost in the early 20th century
when they realized that the same
equations could be used for many many
many different phenomenas the
bell labs people realized that circuits
could be analyzed this way
acoustic phenomena could be analyzed
this way
anything that's got mass and energy
is amenable to this analysis to first
order um
so narendra was in this tradition uh the
the field had gotten a big bang from
weiner in the early part of the 20th
century
everyone thought that cybernetics was
going to be the first synthetic science
you know kinematics in some sense was
the beginning of
kinetics is the study of how for example
how you how you take rotary things and
you get linear
motions out of them or how you take
linear motions and you automate
them to get rotary motions and that had
been
uh practiced by the you know the
windmill kind of people or the
the the sawmill people the water wheel
kind of people had been building
those systems for a long time it became
mathematicized in
by rolo and people like that in france
in the
mid 19th century um
and then if you started to add dynamics
on top of the geometry you begin to get
things like
dynamics and controls cybernetics it
looked like that was going to
emerge as the first real synthetic
science
um
in round about the middle of the 20th
century
the the there was a
revolutionary meeting of
the touring style logical folks
with the mcculloch and pitts style
neuroscientists
together with the electrical engineering
circuits
people um and they invented this thing
um called a phenomenon
computer and they realized that there
was already a theoretical framework
that turing had developed so the
mcculloch and pitts paper was one of the
most important it was a neuroscience
paper but it was
they they recognized that you could
write down a discrete dynamical system
not a continuous dynamical system you
could write down a discrete dynamical
system and
you could you could study a
computational engine
from using this kind of applied
mathematics
so as i guess you guys know this was the
beginning of computer
science and computer engineering which
rapidly took off
from 1946 if you go down you'll see the
antiac
which was developed here in our
department in
electrical engineering at the university
of pennsylvania um
between 1946 in 20 years from at
around the early 60s already
the field of computer science or the
field of computer engineering do
anything how you think about it
began to show up on the gross domestic
product i did a little
investigation once i found with the
advent of the ibm 360 in 1962 1963
you can you you can already begin to see
information technology
showing up as a percentage of the gdp
and the statistical abstracts of the
united states
um it just you know it took off right
you know it's the information age
uh and left in the dust
it left the project of cyber index far
far far
far in the dust because things were not
compositional in the same way we didn't
you couldn't snap things together the
way you could begin to
the abstraction barriers apparently were
clearer
i don't know if they were clear that the
the the mathematics was already in place
to get the abstraction barriers right so
composition
one could begin to build um uh
assemblers
on top of the machine language and one
could begin to start thinking about
compilers on top of the assemblers and
one could
uh whereas we still don't have in the
world of
analog dynamics continuous dynamics we
still don't really know what the
abstraction of barriers
should be i mean we think we begin to
know in my group
you know that's only because my students
are contaminated by me
uh we don't really know i mean none of
us i think know where the abstraction
barriers are much less how to compose
things we don't have a compositional
theory we don't have syntax we don't
have
we don't even have symbols again i think
we begin to know what the symbols are
but
um the whole world of analog
engineering was left in the dust by the
successes of
by the growing successes of the discrete
symbolic
uh computational theories um
which wasn't supposed to happen you know
that
computers uh you would have you would
have thought that
analog computation would be the right
way to go because after all that's what
the animals do and the animals are so
much better
than anything we could build uh but we
just couldn't build good analog
systems whether electronic analog
electronics or analog
mechanical things um so why is that
why is that so much harder
in this infancy of computer science it
was also robotics also got its start so
engelberger whom i'm sure you guys have
heard of
begin to build his company and his you
know his universal
manipulator um so you could say
the aniak moment for robotics was
arguably 1956. if the eniac
in computer science was 1946 then 10
years later
uh unimate robots began to appear
in factories um but it
it wasn't a 20-year period it's only now
that robotics is beginning to have so
hard automation had an impact on the
factory floor
you know in the 70s 80s i didn't even
understand quite as well but robotics
almost
still hasn't really shown up in the
statistical abstracts of the united
states
um
carver mead revolutionized the design of
digital electric
electronic circuits in the 70s at
caltech he did
he developed these ideas about
automating the design of digital
circuits
and that gave rise eventually to the
moses foundry system where you could
design something in cad hit carriage
return and have it come back to you in
physical instantiation
a few months later now a few weeks later
um
he then tried to do the same thing for
analog electronics
a decade later you can read his he's got
this very
he's got these wonderful books conway
mead was this book where he where he and
lynn conway set up the revolution of
digital circuitry and digital circuit
design
and fabrication which
is as important as the theory of
computer science for allowing us to have
what we call the information age right
or the information technology revolution
carver mead then tried to write a
similar book an analogous book for
analog electronics uh
inspired very much by uh nero you know
by
neurosystems and his 1986 book is
wonderful to read but it didn't have
anywhere near the impact that
um that his 1974 book
had his 1974 book gave rise to a
revolution which changed
the human experience and um
so i'm trying to portray for you all the
ways in which
it's confusing to try to understand what
it is about
one kind of technology that's going to
take off
and what it is about another kind of
technology that doesn't
doesn't allow it or can't take off
you know and you'd like to know why it
is that um
20 years after any act there was this
information technology revolution
whereas 50 years after
engelberger we still don't really you
know know what robotics is and you you
could say well those guys were smart and
we're stupid
but you know that's not the explanation
i prefer
it's not my preferred explanation my
preferred explanations there's something
quite different and much much much
harder about analog
design and continue the
engineering in the in the continuous
world
than there is about engineering in the
discrete world and
that's what my students and i try to
study
that it gradually as i became
increasingly sentient you know
when did i become a sentient creature i
don't know when i was 30.
you know so when you were doing your
graduate work was it already clear that
the applications you're interested were
robotics no
no i was uh i thought of that myself as
a control theorist
there and i stumbled on narendra was
working on problems of adaptive control
which roughly speaking is
how could a system learn
what its parameters should be how could
it tune so how could a controller
tune itself up to fit a physical system
that wasn't really
already experimented with if you
experiment enough with the physical
system you'll get the parameters down
and so you can build your you can design
your controller and it'll
you can drop it in but you may not have
the time you may not have the ability or
you may not have the
ex the money
to do a prior experiments on this
physical thing before you need to drop a
controller in
so could you have an adaptive controller
that you'd plug it in it would figure
out
enough about what the nature of this
phenomenon is that
um it could function
so there was a grown theory of this uh
and it turned out that uh part of the
there was a mathematical problem that
arose
that narendra thought could be solved by
a certain
kind of non-linear analysis in those
days people were doing almost
exclusively
linear analysis um
so he got me started on that and you
know we wrote some papers and it was fun
and then it got hard and got harder and
later on it became clear to us that to
solve the thing that he really wanted me
to solve we would have had to answer
one of hilbert's problems that remains
unsolved
most of hilbert's problems turn out you
know either they were solved in the 20th
century or
one or two of them turned out to be
undecidable so
hilbert didn't dream that there could be
such a thing as an undecidable problem
right but
i think his tenth problem turned out to
be undecidable but his 16th problem
uh it remains open as far as i can tell
and and it turned out that what narendra
wanted me to do was
to solve it completely would have been a
corner of a corner of hilbert's 16th
problem which
you know i'm not a good mathematician
not a i'm not a mathematician at all
so uh but we didn't know we didn't
understand at the time
um so it was very exciting a lot of fun
and we published papers and
then it was time then said it was time
to graduate but i didn't want to
graduate
because you know it's much better to be
a graduate student
much much much better as i think you
guys both of you have phds
it's much better to be a graduate
student it's the best
the best thing to read graduates do um
but you know time to grow up he said uh
in uh i hadn't thought it would be an
academic but he thought i should be an
academic
um uh
but it was it was also clear it was
becoming
increasingly clear to me that the field
of control had become sterile
part of the reason that control wasn't
working was that the agenda of
cybernetics had split into things called
control theory communications theory
signal processing and it was all it all
became very as
every part of technical knowledge in the
20th century later 20th century
everything became radically particular
and very
siloed and very specialized and
um it
seems to me that the field of control
almost self-destructed in the 80s and
90s because it became so sterile became
so much a game of
applied mathematics but not necessarily
the kind of mathematics that the
mathematicians would care about
nor necessarily anything that you could
apply in the physical world
it was already clear to me you know ward
narendra was
helping me see that the field was very
mature
the the field of control was very very
mature and it wasn't clear what would be
earth-shaking about
solving yet you know i'm not going to
solve hilbert's problem right that's not
what i'm capable of doing
i'm not a mathematician that's not what
i'm supposed to i'm supposed to be
designing things and that's supposed to
be analyzing things you analyze things
only so you could design them better
if you're an engineer but we were doing
all analysis in their design
um so it seemed like in
narendra sort of said well why don't you
think about robotics
the computation is now available and um
people think that robotics is going to
be a big thing everyone's been working
people wanting to do robots for 2000
years so why don't you work on that so i
that was a great idea
so i started working on robotics as an
application of control
and gradually it became clear that
robotics was not just an application of
control it certainly wasn't an
application of computer science
it wasn't an application of mechanical
engineering
it was at this point that i began to see
raybert's
work on the hopping robots and had a
huge
impact on me to recognize that
his he built a
one degree freedom hopping robot and
then he made it
hop around on a boom and then he took it
off the movie he had a three-degree
freedom hop-in robot and then he could
put
pairs of legs on it and then he had
these systematic
uh deeply intuitive he didn't have any
mathematics
very very little amount of mathematics
that went into his designs
but they were very um compositional
and he was building up more complicated
machines from simpler machines
um it didn't work perfectly they didn't
work perfectly but they worked
better than anything else that had been
built no legged machine had ever ever
balanced uh barely had any legged
machines ever done anything
so that had a huge impact that work that
robert did i think as i've said i think
is the most important work in robotics
of the 20th century
because it showed that the problem of
robotics
is um how to get the power power is
always limited power is always
constrained
uh power density is really constrained
watts per kilogram is really the
limiting the scarce
resource i mean energy is constrained
also but you can always get a new
battery but
actuators you can't get watts per
kilogram
you'll melt before you get enough watts
per kilogram okay so what do you do with
the limit given the
power that you have available to you
what do you do with that power how do
you distribute it and when
so the problem of programming power the
problem of programming
the exchange of energy with the
environment
is really a fundamental problem that
nobody had ever
thought to work on before raybert
realized
he wouldn't say it this way he makes fun
of me for being pompous when i you know
when i talk this way he's not paul and
scott
he's not an academic anymore at all so
you can't afford to be focused but
we're academics i'm popping up but you
know he
he um he really really pointed out that
that problem was a new problem and uh
so we some of my students and i started
chasing that problem and
in the course of chasing that problem it
became clear to me that you didn't
necessarily want to do control
theory what you want to do with control
theory is you want to close loops
and when you close loops you're going to
end up with an analog system
and the question with an analog system
is what are the symbols
how are you going to compose analog
systems
then you begin to realize that no one's
ever really succeeded in
building a compositional theory of
analog systems people
uh people know how to build rls
people in bell labs in the 20s the
artists at bell labs had built rlc
circuits and then there was enough
mathematics done linear
analysis done so that we could teach it
to our sophomores
by the 70s we would teach
analog design using rlc
analysis but that but those are all
linear
dynamical systems they're not
interesting the way
the way that rayburn's machines are
interesting
okay so what so so how do you study this
thing
um then that's what my students i've
any students who work with me and
survive
uh uh end up at least being contaminated
for a while to
agree with me that what we're really
doing is we're trying to understand
how to program work how to take
energy exchange systems and compose them
how to
mold the energy exchange systems and
adapt them
to the physical world and the
palette is a mixture of algorithms and
um design and electromechanical designs
so it so so i'm going to stop and
let you guys get some words in edgewood
because
that's this is now the beginning of my
advent as a thinker and a contributor to
my field
i would say having graduated from my
guru my advisor narendra and
becoming aware of my older brother
raybert's work and how important that
was that was
in my ex that was my
entry point into the into the life of of
the field i would say so what was the
first robot that you actually worked on
that my students and i did be careful
i'm not a good builder or designer
my students are all the people who do
the building and the designing i
i sort of sit back and i you know i i
kits or i
i watch what they're doing and try to
ask them 100 stupid questions
um we then said okay if raybert really
is on to something we ought to be able
to take his ideas and put them in a
completely different
physical form but we ought to be able to
use his ideas
um to get dynamical dexterity in some
very different systems so we said why
don't we do dynamically dexterous
manipulation
well what is that well you know it's
juggling
so we built a series of robot jugglers
so the first machine that we built was
built by martin buehler
in my laboratory
in 87 i guess
it was a it was a one it was it was a
puck sliding on an inclined plane which
could become almost vertical
and that puck got hit by a by a bar and
what we wanted to do is we wanted to
show that rayburt's ideas about his
vertical hopper could be taken
mathematicized
turned into a juggling algorithm and um
that's essentially what we did and then
we built
we showed that you could do this with um
spatial so al rizzi's thesis was
to do the same kind of thing with not a
planar mechanism but with a spatial
mechanism
and then we showed empirically not
not with enough mathematics yet that you
could actually compose these things so
that just like rayburn could have a
two-legged
vertical hopper that began to be a biped
we could have a two juggle
to juggle the robot and we had some
analysis that showed that the designs
were correct
and then we had experiments that would
show that the
analysis was not unreasonable and it was
probably probably the first work in the
field that tried to simultaneously be
theoretical and empirical that we didn't
feel i didn't feel
i still don't feel that the field is
mature enough to support this
division that you'll see in physics or
chemistry you know between the empirical
side and the
theoretical side i think that's a very
dangerous thing
for a mature field to do so i think
probably our lab was the first
to i don't think that there were earlier
labs that brought
new mathematical analyses to bear on new
mechanic new electromechanical designs
and would
have to run experiments whilst running
uh
proofs trying to prove so that's
probably sociologically that's probably
the
the the one of the main contributions
that's come out of my group
um intellectually we've not succeeded of
our purpose so
so sort of sociologically i think the
field is certainly
most people believe that you have to
build things and prove things that you
can't do one or the other
and i i i'm pretty sure that we had made
you know some
substantial contribution to that maybe
it would i'm sure it would have happened
any any anyway
although maybe not maybe the you would
have gone the
world wave control theory where it
becomes either very mathematical or very
pragmatic um but the agenda the
intellectual agenda we've still not
uh i still don't think we've
made the progress that i hoped we would
make which is
understanding what it means to program
work
or what the symbols are we've made some
progress there
and we have better and better machines
but it's hard to argue that those
machines are better because of our
analytical understanding
i think they are better because of our
analytical understanding but it's hard
to argue
that given all the advances in control
in in computational
uh technology and the new in
more recently they've been these
advances in microelectromechanical
systems which give rise to
amazingly good sensors that we never had
before
um so it's
oh well it's hard to know whether
well i think we've i think the i think
the analytical point of view has made
progress but
i don't think we've achieved our
intellectual aim uh
and i guess we won't you know i i'll
probably be retired before
uh before robotics becomes a discipline
of
with a with with very sound intellectual
foundations
what year was the judge
um so ray bert's first hopper was 82
83 i became aware of his work in 84 85
martin came and joined me in 86 he built
his first
mechanism in 87. it began to work in
8788
uh louis
whitcomb came along
and uh built the spatial version and
then al rizzi came along and used the
spatial version to juggle in
89.
at the same time we were beginning to
be more systematic
i had another student at that time a
different student
whose name was rimon ilon ramon uh who's
now the technion
you know it's a small enough field that
you know all of my st you know they're
they all were or they became academics
or they've defected
so bueller now defected from mcgill he
formed a company and then
rayburn bought his brought him out and
then he quit rayburt's company is now
working for irobot and rizzy
you know is now the chief roboticist at
boston dynamics which is
uh it's it's such a small field still
that you get that all these lineages are
still very
uh they look very personal but of course
of course they're really not that
personal they're really
the it's the you know the fields
are much more powerful than any
individual or any school of
thought um uh
but it does it had it
had felt very personal for a very long
time so lon riemann um
started working with me on one of usama
khatib's ideas
usama had done this wonderful work as a
doctoral student
he was the one who figured out that lord
calvin had a good idea
he wouldn't say it this way of course he
would say it a different way but uh
um
lord calvin had this idea that
if you put dissipation into him into a
physical system it's going to decay down
to the rest states of the potential
energy
and usama's idea was um hey
let's use this let's use this to
on the one hand avoid high energy places
and on the other hand seek the low
energy places if we could
encode our goal by making the thing we
don't want to have happen
be high energy and make the thing that
we do want to have happy
happen be low energy then we'd get an
automatic
um task solver
and it would be an energetically
viable pass solve it wouldn't just be a
piece of computation he
never said it this way right this is my
gloss on his
his ideas but they were his ideas and um
we thought you know when we looked at
his what he had done we thought that's
that's exactly right lord calvin was
really an analog computer programmer
even though he didn't think about
himself that way
so uh elon and i
began to work on obstacle avoidance and
came to realize that a lot of the
fundamental limitations had been
that there are fundamental limitations
into uh
of what you can get out of an analog
solver
that have to do with things that
poincare had begun to discover 100 years
earlier in there's this hairy ball lemma
you guys may not have heard of it but
you can comb
you can comb your hair but you're not
going to avoid a cowlick
you just can't avoid the cowlick you
know no matter if you want to be
smoothly combed there's going to be
either a bald spot or there's going to
be a cowlick
and that's a there's a fundamental
topological obstruction
to having smooth fields of arrows or
vector fields as we call those the
mathematicians call them on um
on spheres if you think about your head
as a sphere
um and those constraints begin to give
you a foundation of what you can't
do in analog design if you want if you
believe that your analog design
has to move energy then you're stuck
with
newtonian lagrangian hamiltonian
kelvin style uh systems second order
systems as they're called
their dynamical systems and if they're
going to be dynamically and if you
believe that you
at the lowest level you can only have
access to smooth things so that you
can't do any switching
switching could be done by a computer
but it couldn't be done by
um a spring mass damper system per say
spring last
dampers doesn't have to be even if
they're electrical springs
they have to be smooth they have to
act in a smooth way and then you're
suddenly in this world of the
topologists the topologists have been
studying the limitations of continuous
things
how what what what defects there are if
you're trying to build continuous
systems and when you're going to end up
having
breaks discontinuities necessary
discontinuities
and so those necessary discontinues
begin when you squint your eyes they
begin to look
like um symbols they you begin to get
discreet phenomena so then that's of
course the topologists did that they
realized oh well
it's not enough to do continuous things
you have to understand the
um combinatorial nature of the way in
which continuous things fit together
it's ineluctable that you will have
discretized
components if you're going to try to
build things out of continuous
pieces and so that's so that was called
combinatorial topology in the in the
early part of the 20th century it became
algebraic topology in the later part of
the 20th century
and it's now you know now there's a an
emerging field called
uh computational or applied algebraic
topology
which we're beginning to benefit from
immensely but
it was the first time that i saw in my
worrying about where the symbols were
going to come from that there was a very
very very deep
foundational principled way which you
couldn't avoid the symbols
if you committed yourself to smooth
dynamical systems
and how why would you do that you would
do that because you realize that you
have to
program energy and newton says you can't
program energy without f equals m a
there's no way you're going to get
exchange of energy without dynamics
there's no way you're going to have
dynamics without smooth or continuous
things
and the topologists tell you that their
constraints their obstacles their
obstructions
to to the way in which things can be put
together
in the continuous world and still be
continuous you can't
so that was the domain
of inquiry that elon got me started on
when he was my
when he joined my lab so on the one hand
we were watching
rayburn build these energetic systems
and program
and manage energy in his systems on the
other hand elon was showing me that
we didn't have an algebraic topology at
that point but we became
clear that there were these constraints
that are these obstructions that you
couldn't avoid
when you tried to do what usama had said
osama did only a local version of
someone said oh let me try to get to the
let me try to get to the bottom let me
try to
get my glasses without hitting the table
and we said okay let's just let's do
that globally let's try to
build let's try to set up a field so
that the robot would walk into the room
and not only would grab the glasses but
would from anywhere in the room would
be able to avoid all the chairs in the
room all the tables in the room and not
bump into any people
and and moved down to get glasses using
usama's ideas
and eventually you see that there are
topological obstructions to doing that
and so the topological obstructions
imply that you're going to end up with
um discretized
discrete sub components of the space you
have to begin to break the space up into
chunks and
we don't know what those chunks should
be you know there will be chunks and so
you don't know what the symbols are but
you know there will be symbols if you
pass from signals to symbols
at the at the threshold of analog to
you from from continuous to discrete
representations of
things um and so you know that was
this was now by 88 89 we were building
juggling machines any line and i was
proving things as my graduate student
about
what what kind of obstacle avoidance
functions you could have what you
couldn't have
you know and uh that that's what i've
been doing ever since i guess you know
you have an ex
you have an explosion of understanding
in your
30s 20s and 30s and then maybe you turn
into a broken record you know i mean
that's
that's that's what i've been trying to
do for the last 25 years
trying to take those ideas and really
really
um show that they're
necessary discover how they're not
sufficient
i'm sure they're not sufficient um
try to learn enough mathematics which is
always very hard for me
so that we can use what's known by the
mathematicians
try to make the best use of technologies
it rapidly emerges
so that we don't so that we do the best
experiments that we can do
um and you know we're always behind or
never
it's never i've had wonderful wonderful
students
and you know each of them almost all the
students have done things that
you know we are we produce pretty good
good uh high highly cited papers
um and a lot of them have become
professors in their own right
um and we still don't have a claim
not only is my group not touring but
none of my students
i would say yet have shown that their
students are going to be touring
or the touring equivalent
so that was i guess the second chapter
for me and then
you know the last chapter was when i
started thinking about animals and
biology
but that's it that was a later there's a
later chapter so
so i'm talking and i think i'll shut up
and give give you guys
some room to so how did you get
interested then and
more in the animals or going from
manipulation to locomotion
oh well because well locomotion it's
clear that roblox are supposed to walk
right so rayburn you know we we thought
well someday we'll be smart enough to
beat rayburn at his game
right so that still hasn't happened but
you know
maybe someday that will happen but
animals i mean everybody knew that the
animals are
better right anything that we can build
the animals can do better
um but it's very hard to study animals
um
the traditions of engineering had been
that
you've got two polls of design one pole
is experience and the other pole is
authority you know that you learn as an
english major you learn
in chaucer you reach us or is there's
this war between experience and
authority right you know that
and in engineering this this uh this
tension is very strong between the
people who are intuitive designers
who can just build it get out of their
way and
um they'll build something that'll be
really really good
um as distinct from not necessarily
opposed to
often opposed to but not necessarily
opposed to distinct from
the um the
analysis people are going to study the
thing that was built to try to
model what was built try to see what the
flaws were
try to see try to reason mathematically
about
what could have been done better or how
to generalize this thing even if you
couldn't build it better can you
generalize it or could you take it away
from the
world of artistry and turn it into the
world of synthesis
you know um
and what i guess what became clear to me
somewhere in the 90s was the
as biology became more quantitative and
more accomplished scientifically
there was the prospect that you could
have a third poll of design
which would be
if not copying which is a very foolish
thing to do
um uh at least inspiration that you
could at least
as a third pole of synthesis which we
hadn't
really thought of before that you could
try to extract
principles from working devices
you could try to use existence proofs
and you tried to you could try to
actually
do more than just watch them you could
try to
experiment with them and try to
understand you could try to
assert hypotheses about
what it was they were doing or what it
was they couldn't possibly be doing and
you could try to refute those hypotheses
and you would be advancing biology if
you did it well and of course you would
be greatly
deepening your understanding of what
your design could look like in in a
in a way that was neither experience nor
authority was neither using mathematics
to reason purely from a formal point of
view
nor was it using your deep your students
not mine but when students deep
intuition about
how to build things or what could be
built so it's a third pulse so it's
emerging so this idea that by
inspiration
is emerging as a third pole of design
greatly enriching engineering
a lot of foolery about it a lot of
um not so much intentional but a lot of
clackery that unnecessary unfortunate
quackery about
oh you know the cockroach has these
little hairs and so we're going to put
these little hairs here
you know but the cockroach is a has
constraints that
that artifacts don't have the cockroach
has to reproduce the cockroach has to
eat the cockroach has to
develop and mold and you know and there
are these historical accidents that are
very very
um it's very hard to understand whether
that hair is there because it's
functional
in locomotion or whether it's there
because the cockroach also has to
mate and reproduce um
that was so it's very clear how
treacherous bioinspiration is
biomimicry is never going to work and
bioinspiration's very treacherous and so
i you know it was important if we wanted
to take that seriously it was important
to find
biological as important as it is to have
mathematical collaborators it would be
very very important to find
really really really powerful biology
collaborators otherwise you're not going
to
you know it was clear to me that you're
not going to do very much interesting
there's this what were some of the
biologists you collaborated with
the most the guy who's taught me the
most is bob full at berkeley uh
he's taught me immense number of things
um
he understands mechanics certainly
better than i do
he's a bi he started life as a
biomechanics guy but he's
quite a bit broader than that um
and he had been um
how long are you gonna go ahead and keep
this on me i'll talk the whole afternoon
i just let me understand what mine when
is my next name
okay um let me just see what my
constraints are i think i'm
okay till 130 but what happens at 130.
i'm the chairman of the department you
know so my life is not my own anymore
oh no i'm okay i left us till two okay
so you're my pumpkin is your pumpkin um
okay so i'll i'll monologue on for
another 10 minutes and then i think
maybe
it would be better for me to to be more
interactive in the discussion to
try to make sure that we're getting in
directions that you think
useful um
bob came out of a tradition of
biomechanics that tried to understand
why it is he came from two different
traditions that were
both immensely appealing to me one of
his traditions
was um what are the energetics
tell me what it costs to run tell me
what it costs to walk
tell me and and let's measure the oxygen
so so
miles per gallon for biology is measured
by metabolic
rate how much oxygen you know what
you're doing with the oxygen so you know
they could measure it under controlled
enough circumstances so he came out of
that tradition of trying to understand
what the animals know how to do with
their energy
he also came out of a
tradition that said it could be that
it's not
just the energetics that's a constraint
it could be that it's the control
of the of the behavior that's a
constraint
and the intersection of those ideas was
a
tendency in biomechanics to try to so
it's an empirical fact that whether
we run over a scale as humans or whether
birds are over the scale or
mountain goats run over scale or
elephants and over the stuff they if
they're running
if an animal is running over a force
plate a scale
and you look at the ground reaction
forces that
the scale is reporting you'll see
something that looks a lot like a pogo
stick
um rayburst swears that he doesn't know
he didn't
read the bio literature here you know of
course i believe him
he's very very brilliant guy so you know
he doesn't need that maybe he doesn't
need math he doesn't need biology
um but there was this long tradition
going back into the 50s
of studying the way in which animals
when they run when they're locomoting
very
in a very dexterous dynamical way they
fool the ground into thinking that
they're pogo sticks
bob full had spent a lot of his career
measuring animals and trying to
see whether this is just approximately
true or how exactly it was true
so my way of getting his attention was i
could give him ideas about how to
identify
i had to do even more you know i know
about dynamical systems and pogo sticks
are dynamical systems and i could help
him
think about how to measure whether his
data really was anecdotally or really
was exactly a pogo stick
um and then of course he could be
enormously helpful to me
uh thinking about how would you probe
the animals if you're going to try to
figure out whether they're really
controlling
themselves to be pogo sticks or whether
it's just some accident because after
all
an animal like a human the mass is way
up here
and the legs don't have very much mass
and the tendons are kind of springy and
so isn't it obvious i mean is this is it
so surprising that
that that when we run over a force plate
the force
the scale thinks that it's a pogo stick
but then you start thinking well wait a
minute the cockroach is also full of
scales i think that and the cockroaches
don't look at all like a pogo stick
all right there's other people who who
think that this is obvious
and that to the extent that it's true
it's obvious and to the extent that it's
um more mathematically careful that it's
not true
um and then the people who like me who
think
yeah it's when you start really really
pushing these are not hamiltonian
systems like a pogo stick
ideally would be a lossless system but
the metaphor of a pogba stick is such a
powerful and and useful
thing that we should try to capitalize
on the ideas of dynamical systems theory
and begin to set up a whole
maybe house of cards maybe house of
stone like to be
we'd like to have flashy things that you
know in those days there wasn't youtube
and
you know the but by the time rex came
along they began to be slashdot in the
old juggling days
it wasn't even slashdot so we wanted to
be flashy but we couldn't be flashy
um uh
and um
that's essentially what we've been doing
we've been taking these these directions
and we've been trying to uh be careful
about them
and trying to advance
the field and trying to understand what
the fundamental limitations would be and
why it's so
hard to get your hands on the
fundamental problem of robotics or
not just robotics but any you know
analog circuits neuro mechanics
if you're trying to do systems biology
at the organismal level
these problems all begin to come
together if you take this point of view
and they're really really hard and uh
we're
you know we're scratching we're
digging i would say more than scratching
source we're digging into the surface
but
but only only only very slowly
how did you end up meeting or learning
about
his work
yeah you'd think i would know that oh
i'm just scared because it's a different
field so i was just curious
yeah you know i i should i should have
that
i should know that i mean i know let me
just just
think about that for a minute
i had a student bill schwind was writing
a thesis
on the hoppers
and somehow we became aware that there
was this biology literature
on pogo sticks i can't remember
how we became aware of that and as soon
as we became aware of that
you know bob full is the king of that
world and so
you know you wanted to talk to the if
the if the king will will receive you
then you want to talk to the king
and fortunately you know luckily for me
bob was willing to
spend time uh talking yeah so that i i
think that's what happened that we
realized suddenly that
the biologists are also thinking about
these things from a very very different
perspective and
and who are the biologists well it goes
back to cavania and taylor in the 60s
and 70s
and who are the people who are doing it
now oh it's bob full and
uh reinhard blickhand and bob's students
and
so i think that's how i think i'm i
could check and try to be more
careful and i think that's true so when
did you first come to
upenn and who else was doing robotics
when you came here and how did you
i came here because all my friends so i
was at university of michigan for a very
long time
which is a wonderful wonderful powerful
great uh school um
i uh
came here because uh
robotics was very strong here robotics
is not
everything is strong in michigan
michigan is the third fourth fifth
strongest engineering school in the
country depending on who you ask
you know what field you're talking about
um
i had not been very successful in
getting colleagues at
michigan to to be to think that robotics
was
was a field people respected my work
they liked me they treated me
enormously well i i have friends i love
the place i love my colleagues there
i love them i mean it's just a wonderful
school
but
i think i was considered to be
hair brained um not hair
uh as a as
uh you would never entrust codecheck to
hire people
because karachik had such idiosyncratic
ideas about
where to go on the one hand and on the
other hand you would never
make the mistake of thinking that
robotics was something that would be a
fundamental
problem domain it would be something
that every engineering school needs to
have
but um
it's a it's a place where computer
science meets mechanical engineering
meets electrical engineering
that's what it is it's a technology and
um you know kardachik has these
affectations that we'll forgive that
they're not
you know we will forgive them because
you know he brings in enough grant money
and he publishes enough papers and he
turns out students
um but at penn uh
simultaneously they had formed a new
department
they had taken two old departments
electrical engineering and systems
engineering they had formed a new
department called electrical and systems
engineering
and they were they were looking for
chairman
and at the same time penn was a place
where um
some very very important the only more
important place in
in robotics has been cmu arguably before
i showed up
know not not not with me here um that
the
the cmu is larger remains larger but the
intellectual density at penn
in robotics was very very pronounced um
i was very scornful i remained very
scornful about academic officers i've
always
told my students that chairman of
departments are pathetic
that i would never ever ever do such a
thing because you have all this
responsibility and no power at all
it's it's absurd to be an academic
officer i have always felt
i still pretty much feel it but um
uh but the dean here is very unusual
you probably won't meet the dean you
must be talking to other people you can
talk to vijay kumar
you can talk to mark iam martial
very important guy modular robotics
modular robotics very important guy i
know i know of his work
actually yeah it's pretty important yeah
we have george papa
george is very important guys what do we
have today
oh we have costa costas is a very good
guy
uh a lot of the folks uh here
are really you know long before i showed
up penn was
um one of the most important places for
robotics
part of the reason that penn took off
was because regina baichi whom i'm sure
you have
gotten to know you know she had uh
you know she started the robotics group
here
it's her thing she you know uh
i'm just a transient you know um
part of the reason that she could be so
successful was because she's so smart
and capable
but um at the time that that the place
was really taking off
she had been working hard for decades
but certainly my whole career she's been
out in front but in
uh you could argue that the dean here
has been extraordinarily important for
robotics and for many other
uh endeavors so i met this guy and i've
had
i've worked with a lot of deans but this
guy who eduardo glant
i've never met a person like this and he
said well why don't you come and you can
you know you'll hire all sorts of people
and you'll redefine what what
electrical means and what systems means
and
you know we'll still let you do robotics
but um
uh so i found him uh very beguiling and
i broke my
promise to my students that i would
never waste my time
in academic uh management which is
uh so so i came for those
two reasons they uh uh
you know the in academia it's very hard
to my wife is a
professor and it turns out the dean of
the nursing school fell in love with my
wife and you know i couldn't have come
if that hadn't happened
so that that all worked out so what year
was that
2004. and how long were you at michigan
1990 to
uh 1993 to 2005. i
officially left i came here in the 404
and then i
took i accepted the position in general
05
yeah and before that i was a professor
at yale i
uh i was i was in 1980
i got my degree my doctoral degree in
1983
and i was hired on the faculty in 1980
three
yeah you were there until 87 no
i was there until 1992
yeah yeah
so yeah so pen is uh
well pen is a really important place in
robotics it's
probably well
you know we'll have to do better we'd
like to overtake cmu but our friends at
cmu are so wonderful that you know they
have the head start and they're
they're they have wonderful wonderful
people there too but certainly
certainly erosion i got got something
off the ground here that that very very
very few people
have been able to pull off i was not
ever going to be able to accomplish
anything like that in michigan
russia probably could have i couldn't
yeah you also i think um regis reading
through your
cv had some connections with japan
yeah yeah
oh yeah japan is really important uh
i mean since i've been chairman i've
been traveling very little
uh well you know
i haven't been to japan recently um
uh i haven't been anywhere recently i've
been here
being a chairman um
in those days we thought that japan
this was before japan's bust and it
looked like
we watched japan in the period of the
80s you could see japan emerge from
being a developing country to a
developed country where the cars would
get bigger
every year and the clothing would get
more expensive every year and the food
would get
more lavish every year this was in the
80s and i was traveling
once a year twice a year sometimes three
times a year
and wonderful that they were wanted they
were just wonderfully
hospitable it was clear that they had
ideas about robotics that were quite
different from ours
they were interested in our ideas we
were fascinated in their ability to
build things
um and it's
really well particularly now we feel so
bad for our friend you know our friends
and our colleagues have suffered
so terribly with the uh with the uh with
this disaster
but the the economic disaster also hit
them very very badly
and um
hasn't stopped the development of
robotics in japan but
really slowed it down really slowed down
a lot of stuff that was going on in
japan
um i mean i you know i would be i would
continue to travel there if i
traveled at all i don't travel hardly at
all right now
um so how did you become
involved with them did you meet somebody
or what was yours
yeah the historically the thing
uh i guess the the closest connection
that usama and i still have is
he's he leads this uh
international federation of robotics
research which in
our day was the most important
international
locus of robotics and it was the only
place where
the three continents really tried to
have an exchange in a formal way
and um the japanese were very very happy
so regina and
and and her generation had been very
uh careful to work with the europeans
and with the japanese to set up this iaf
or
or which was some instant the president
of uh
and so i met the japanese researchers
because
the regina and her generation were so
supportive of my generation they brought
me in
they brought me to the meetings they
introduced me to these people
very not not always will the
main figures in the field be so
accommodating and have such an idea that
mentorship for their younger
cohorts as brujan and her cohort and her
colleagues
uh very unusual takeo canada you know
these people i'm sure you've
heard their names in addition to being
you know wonderful fabulous scientists
they were extraordinarily careful
about the uh field about creating a
field and creating the circumstances in
the field so that young people could be
could move ahead and
could get careers and
i don't think that i have been or
maybe my generation certainly not i have
not i have not been as careful
i've done very well with my own students
i think but
i don't think i have been as attentive
to the field as they were usam has been
right the psalmist has osama has that
idea
and i probably haven't um and maybe my
excuse as well it was really important
then it's not so important that because
the field
but you know that's just an excuse yeah
so so it was rojana
and takeo and bernie roth and that
generation of people who introduced me
to the japanese researchers
who's now a national treasurer in japan
and um
uh his students and uh
arimoto who's retired now had huge
impact on my
thinking he's probably the guy who's
closest to me
intellectually um
yeah they were really really really
important to us they were very they have
been very important in the field
and they've slowed down because this the
country has been slowed down
but yeah so where were you when you were
in japan
i spent most of my time in arimoto's lab
at
tokyo university i spent some time he
arranged for me a tour of the whole
country i met all that generation of
roblox people
in that tour that he arranged arimoto is
another one of these guys
you know ue arimoto these people also
had this idea of
international exchange and preparing the
next
generation of people you know as i speak
about it i have to say i have not been
nearly
i've not been nearly as thoughtful
as that as those guys were about the
international exchange and about the
the establishing mechanisms in the field
yeah these guys were just incredible
they
yeah i mean the field exists probably
because of that generation
it's been it's i think a lot of the
academic
um the rapidity of the economic of
intellectual developments and
cross fertilization has been because of
their because of the talent they set
yeah yeah are there other roboticists
that you've collaborated with
over the years well i guess my most
important robotics collaborators have
been my students
i certainly would be nothing i would
like i would have not been able to build
anything
some of them have been all of them are
better
builders and designers many of them have
been better applied mathematicians than
i
well you know i i've asked good
questions i think that's my
probably my claim that i have i ask
really provocative questions i think
um who have i collaborated with um
who's who's not a student i've er
mainly people who are orthogonal i guess
mainly i've not collaborated with people
in the field i've collaborated mainly
with people outside the field who i
thought
would be would bring tools i didn't have
i collaborated pretty closely with
robert greist who's a computational
topologist who's also
making discoveries in robotics and
domains that you might want to talk to i
don't know if he's here now but
he's a pretty unusual guy he's one of
the spearhead
leaders of this computational topology
he's got a joint appointment in
mathematics and engineering
i collaborated with him pretty closely
because of his mathematical
i wrote papers for some papers with
morris hirsch who is a mathematician at
berkeley
who had a large impact on my thinking
um
bob full his students dan goldman
i've sent him my students he sent me his
students you know my students have been
postdocs in his life his students have
posters in my lab
um i don't know if we invented the word
neuromechanics but i
think many people would credit us for
having created that
that domain or that group of students
and
people um
yeah it's you know it's interesting i
think mostly i've
collaborated with people not in my field
i've collabed with people outside maybe
because i'm so
pig-headed about what's the right way to
do the work and you know i think it's
probably hard to collaborate with me if
you're not my student if you're not in a
different field or maybe i'm just
so frenzied about getting it right and
doing you know doing
yeah yeah that's interesting i had done
that
yeah just to kind of wrap up since we're
um what do you think are some of the
challenges for the future and where do
you think in robotics yeah where do you
think the field is going and when you
think about challenges i mean it can be
intellectual
technological social you know any of
those that you think are
so so intellectually i think we still
don't have good understanding of
why power density is is a scarce
resource
and there ought to be some thermodynamic
reason for this that nobody seems to be
i don't know i don't know what it is and
i don't seem to have the right
um equipment to get my hands on it so
intellectually
those kind of problems we don't we still
don't know what it means why robotics is
a field
how it is that what it is that makes
robotics different from i mean
they're people like me who claim to know
but i haven't delivered on that claim
and then they're people who don't think
there is such a thing so so there are
those intellectual
problems that really really have not
been addressed
properly um then there are technological
opportunities that were
that are represent immense challenges
that
we have the possibility of
so the world of perception is
wide open for robotics the world of
computer vision has been in a morass
because no one can define what the
problem of computer vision is whereas in
the
in robotics it's not computer vision
it's robot vision
and the job of perception is to close
loops around things
all right and so and it and it hasn't
been up until recently that we had the
technology to enable us to be
empirical about those kinds of problems
because you couldn't do things in real
time that involved real
sensing now you can do these things you
know the computation showed up in the in
the in the 80s and 90s and the
sensors showed up in the 90s and the
auths and you know so now
the only thing we lack is power density
we don't have good enough actuators
that's not going to change um but we do
have
uh sensors and the problem of perception
the problem of robot perception is
just wide wide wide open and
you know many many good the best people
in the field i guess are working on i'm
i'm trying to uh reform myself and turn
myself into something of a perception
person that's very painful
so it's not it's not how i but so so
technologically speaking i think the
time is
now everyone understands that the time
is upon us now to try to make to try to
understand
robot perception in a combination of
empirical and mathematical
uh ways um and so that's happening and
that's gonna happen
uh you know sebastian is really really a
powerful thinker in that domain has made
major contributions in that domain
and um uh who else
a lot of the younger people younger and
more more agile than i am
are doing great work and hopefully i'll
be able to
catch up so technologically i would say
that's a very important uh
doing the other thing that's happening
in robotics right now is that we're
probably
we're probably reaching the ibm 360
moment
probably we've thought that we got there
before but it looks like
the robots are going to become useful
not
just to military
they're probably going to come become
useful to police departments and fire
departments
and to
not just automation in companies but for
more flexible very very flexible
automation for biological automation
in biological laboratories and so the
advent of commercial robotics as
represented for example by raybert's
company
where i robot you know i robot kind of
got there first but i don't think they
have quite the
cutting edge you know rayburn's company
has has
i think well they've raved to start with
but
they're um thinking it had to
commercialize
uh these very very elaborate
technologies that if you look at them
you think they couldn't possibly
you could have that in the laboratory
you know it's like this kind of thing
you could have in a laboratory but no
one would ever ever pay any real money
for it because it would break after a
day or two um
so that so that's happening and that's
got to have an impact the way
it's going to have positive and negative
impacts for academia the way that
the revolution computer engineering
demolished a lot of
computer engineering a lot of research
in computer engineering got
ripped out of the universities and and
trapped in the
in the big in intels and the amd's and
that's happening and that's probably
happening robotics right now and
there's there'll be it'll change the way
we think about research
um so you know i mean we we could go
into greater detail on any of these
three but i would say those are the
three you know sort of if you think of
the
intellectual problems the sort of the
the technology opportunities
and then the and then the social impact
that we're about to start having i think
those are the three big
pieces of news for this coming decade
can you talk a little bit about this uh
this one this is uh this guy okay so
well this is
uh this is the 2001 uh rex that
martin buehler built yeah this is this
was built by uh
who's now a professor at duke kent
university in turkey he and martin built
this uh martin bueller was a professor
at mcgill we were collaborating together
on a darker project and this is the
first machine that ran
um at more than anything close to a body
length per second the first machine that
ran over ground that wasn't level
um yeah this is the first
legged machine that has actively tunable
compliance this is a
phd thesis supervised by
mark yim by my former post-doc
jonathan clark who's now a professor at
florida who was a student of uh
markowski you surely are going to talk
to mark coskey yes is he on your list
he's at stanford mark yeah okay
you've got to talk to him he's a
brilliant brilliant mechanical designer
so this is the first that we're trying
to make the com
so a lot of the algorithm for the robot
is not in the
cup in the digital computation but in
the analog
spring mass damper and so this is a this
was the first system to be
actively tunable the compliance or the
springings could be active
this is a
project that was also supervised in part
by jonathan clark
is the phd dissertation of uh
gordon lynch it was the first dynamical
climbing it's the first
so we built a rise robot with bob full
and mark
koski and a couple of other people um
but this was the first vertically
climbing machine to be dynamic to
actually use kinetic energy
so those i guess are my favorite i i
mean i have jugglers but
the jugglers we couldn't afford to keep
you know they take take up too much
space so
those these are my i guess my favorite
uh creatures from the from the past
and have you seen him applied in kind of
real world circumstances yeah i mean we
you know if i were a better researcher
we would have
this thing would have been
commercialized by now
uh it should have been used uh in search
and rescue it should have been
it should be out in the field by now um
it's probably still the price
performance
is still not good enough apparently
so i mean search and rescue surveillance
obviously military leggett machines have
the ability to manipulate as well as to
locomote
yeah i'm disappointed that we haven't uh
i've seen two rounds of companies come
and go with trying to commercialize
these technologies
and uh i i'm really good at certain
things and i'm apparently really not
good at uh
commercialization so what's your advice
to
young people who want to get involved in
robotics
um
the dream don't lose sight of the
uh
focus on the science fiction and what's
cool and why we still are not cool
try to be driven by how uncool
robots are right now and how the animals
and how science fiction imagination
about
robotics is is cool and why is it that
we're so pathetic
so try to really keep in sight try try
to postpone the day that you become just
a person to publish papers and
try to keep your eye on how
amazing it would be to have real robots
and then you know you have to
if you really want to make a dent in
that way you have to
you have to become an expert at least in
something you have to be
you have to have deep expertise either
in computer science or in mechanical
engineering or in electrical engineering
or in mathematics
but that's not or we're in biology in
neuroscience
increasingly it's becoming important but
in robotics that's not it's not enough
to just be an expert you have to be an
expert
in something otherwise you'll never make
it but you also have to
know a lot about these other disciplines
you have to really really commit
yourself to
interdisciplinary studies in a very
painful very very painful way
um and so it's still a very treacherous
field for young people
and you need to young people need to get
really good mentors
and um the the old guys on women need to
be
they need to be like and take a canada
they need to be really careful about
um uh taking care of and
and bringing bringing people along
because you can
you can become just a gadgeteer or you
can become a sterile applied
mathematician or you can become
you know there are many many many ways
to go wrong in this very complicated
domain so yeah i would say the first and
most important thing is
don't ever lose sight of how pathetic it
is what we can do
and how how huge it would be if we could
get
and then the second thing was and look
at the immensity of
knowledge that you're going to have to
gain and the kinds of collaborations
that you'll have to
undertake in order to really realize
that
yeah that's it i strangely hadn't
thought about that question
thank you thank you thank you so much i
really appreciate your
effort and if we can be helpful to you
you know