Kind: captions
Language: en
the following is a conversation with
russ tedrick a roboticist
and professor at mit and vice president
of robotics research
at toyota research institute or tri
he works on control of robots in
interesting
complicated underactuated stochastic
difficult to model situations
he's a great teacher and a great person
one of my favorites at mit
we'll get into a lot of topics in this
conversation from his time leading
mit's delta robotics challenge team
to the awesome fact that he often runs
close to a marathon a day
to and from work barefoot
for a world-class roboticist interested
in elegant efficient control
of underactually dynamical systems like
the human body this fact makes russ
one of the most fascinating people i
know
quick summary of the ads three sponsors
magic spoon cereal
better help and expressvpn please
consider supporting this podcast by
going to magicspoon.com
lex and using code lex at checkout going
to betterhelp.com
lex and signing up at expressvpn.com
lexpod click the links in the
description
buy the stuff get the discount it really
is the best way to support this podcast
if you enjoy this thing subscribe on
youtube review it with five stars nappa
podcast
support it on patreon or connect with me
on twitter
at lex friedman as usual i'll do a few
minutes of ads now
and never any ads in the middle that can
break the flow of the conversation
this episode is supported by magic spoon
low carb keto friendly cereal i've been
on a mix of keto or carnivore diet for a
very long time now
that means eating very little carbs
i used to love cereal obviously most
have crazy amounts
of sugar which is terrible for you so i
quit years ago
but magic spoon is a totally new thing
zero sugar
11 grams of protein and only three net
grams of carbs
it tastes delicious it has a bunch of
flavors they're all good
but if you know what's good for you
you'll go with cocoa my favorite flavor
and the flavor of champions click the
magicspoon.com
lex link in the description use code lex
at checkout to get the discount
and to let them know i sent you so buy
all
of their cereal it's delicious and good
for you
you won't regret it the show is also
sponsored by
better help spelled h-e-l-p-help
check it out at betterhelp.com lex
they figure out what you need and match
you with a licensed professional
therapist
in under 48 hours it's not a crisis line
it's not self-help it is professional
counseling done securely
online as you may know i'm a bit from
the david goggins line of creatures
and still have some demons to contend
with usually on long runs or
all-nighters full of self-doubt i think
suffering is essential for creation
but you can suffer beautifully in a way
that doesn't destroy you
for most people i think a good therapist
can help in this
so it's at least worth a try check out
the reviews
they're all good it's easy private
affordable available worldwide
you can communicate by text anytime and
schedule
weekly audio and video sessions check it
out at betterhelp.com
lex this show is also sponsored by
expressvpn get it at expressvpn.com
lexpod to get a discount and to support
this podcast
have you ever watched the office if you
have
you probably know it's based on the uk
series also called
the office not to steer up trouble but i
personally think the british version is
actually more brilliant
than the american one but both are
amazing anyway
there are actually nine other countries
with their own version of the office
you can get access to them with no geo
restriction when you use
expressvpn it lets you control where you
want sites to think you're located
you can choose from nearly 100 different
countries
giving you access to content that isn't
available in your region so again
get it on any device at expressvpn.com
lexbod to get an extra three months free
and to support this podcast and now
here's my conversation with russ tedjerk
what is the most beautiful motion of a
animal or robot
that you've ever seen i think the most
beautiful
motion of a robot has to be the passive
dynamic walkers
i think there's just something
fundamentally beautiful the ones in
particular that steve collins built with
andy rowena
at cornell a 3d walking machine
so it was not confined to a boom or a
plane
that you put it on top of a small ramp
give it a little push
it's powered only by gravity no
controllers no batteries whatsoever
it just falls down the ramp and at the
time
it looked more natural more graceful
more human-like
than any robot we'd seen to date powered
only by gravity
how does it work well okay the simplest
model is kind of like a slinky it's like
an elaborate slinky
one of the simplest models we use to
think about it is actually a rimless
wheel
so imagine taking a bike's bicycle wheel
but take the rim
off so it's now just got a bunch of
spokes if you give that a push
it still wants to roll down the ramp but
every time its
foot its spoke comes around and hits the
ground it loses a little energy
every time it takes a step forward it
gains a little energy
those things can come into perfect
balance and actually they
they want to it's a stable phenomenon if
it's going too slow it'll speed up
if it's going too fast it'll slow down
and it comes into a stable periodic
motion
now you can take that rimless wheel
which doesn't look very much like a
human walking
take all the extra spokes away put a
hinge in the middle
now it's two legs that's called our
compass gate walker
that can still you give it a little push
starts falling down a ramp
looks a little bit more like walking at
least it's a biped
but what steve and andy and ted mcgear
started the whole exercise but what
steve and andy did was they took it to
this
beautiful conclusion where they built
something that had knees
arms a torso the arms swung naturally
uh give it a little push and that looked
like a stroll through the park
how do you design something like that i
mean is that art or science
it's on the boundary i think there's a
science to getting
close to the solution i think there's
certainly art in the way that they
they made a beautiful robot but
but then the finesse because because
this was work
they were working with a system that
wasn't perfectly modeled wasn't
perfectly controlled
there's all these little tricks that you
have to tune the suction cups at the
knees for instance so
they stick but then they release at just
the right time or there's all these
little tricks of the trade
which really are art but it was a point
i mean it made the point
and we were at that time the walking
robot the best walking robot in the
world was honda's asimo
absolutely marvel of modern engineering
it's 90s
this was in 97 when they first released
it sort of announced p2 and then it went
through it was asimo by then
in 2004 um
and it looks like this very cautious
walking
like you're walking on on hot coals or
something like that
i think it gets a bad rap asimo is a
beautiful machine it does walk with its
knees bent
our atlas walking had its knees bent but
actually ezimo was pretty fantastic
but it wasn't energy efficient neither
was atlas
when we worked on atlas none of our
robots have
that have been that complicated have
been very energy efficient
but there was a there's a thing that
happens when you do control
when you try to control a system of that
complexity you try to use your motors
to basically counteract gravity
take whatever the world's doing to you
and push back
erase the dynamics of the world and
impose the dynamics you want because you
can make them simple
and analyzable mathematically simple
and this was a very sort of beautiful
example that you don't have to do that
you can just let go let physics do most
of the work right and you just have to
give it a little bit of energy this one
only walked down a ramp it would never
walk on the flat to walk on the flat you
have to give a little energy at some
point
but maybe instead of trying to take the
forces imparted to you by the world
and replacing them what we should be
doing is letting the world push us
around
and we go with the flow very zen very
zen robot
yeah but okay so that sounds very zen
but you can i can also imagine
how many like failed
versions they had to go through like how
many like
i would say it's probably would you say
it's in the thousands that they've had
to have the system
fall down before they figured out how
they could i don't know if it's
thousands but uh it's a lot it takes
some patience there's no question
so in that sense control might help a
little bit
oh the abs i think everybody even at the
time
said that the answer is to do with that
with control but it was just pointing
out that maybe the way we're doing
control right now
isn't the way we should got it so what
what about on the animal side
the ones that figured out how to move
efficiently is there anything you find
inspiring or beautiful in the movement
of anybody i do have a favorite example
okay so it sort of
goes with the passive walking idea so is
there
you know how energy efficient are
animals okay there's a great series of
experiments
by george lotter at harvard and mike
tranifilo at mit
they were studying fish swimming in a
water tunnel
okay and one of these the type of fish
they were studying
were these rainbow trout because they
there was a
phenomenon well understood that rainbow
trout when they're swimming upstream at
mating season
they kind of hang out behind the rocks
and it looks like i mean that's tiring
work swimming upstream
they're hanging out behind the rocks
maybe there's something energetically
interesting there so they tried to
recreate that
they put in this water tunnel a rock
basically a cylinder
that had the same sort of vortex street
the eddies coming off the back of the
rock that you would see in a stream
and they put a real fish behind this and
watched how it swims
and the amazing thing is that if you
watch from above
what the fish swims when it's not behind
a rock it has a particular gate
you can identify the fish the same way
you look at a human looking walking down
the street you sort of have a sense of
how human walks
the fish has a characteristic gate you
put that fish behind the rock its gate
changes
and what they saw was that it was
actually resonating
and kind of surfing between the vortices
yeah
now here was the experiment that really
was the clincher because there was still
it wasn't clear how much of that was
mechanics of the fish how much of that
is control
the brain so the clincher experiment and
maybe one of my favorites to date
although there are
many good experiments they took
this was now a dead fish um they took a
dead fish
they put a string that went that tied
the mouse of the fish to the rock so it
couldn't go back and get
caught in the grates uh and then they
asked what would that dead fish do
when it was hanging out behind the rock
and so what you'd expect it sort of
flopped around like a dead fish
in the in the vortex wake until
something sort of amazing happens and
this video
is worth putting in
right what happens uh the dead fish
basically starts swimming upstream
right it's completely dead no brain no
motors
no control but it somehow the mechanics
of the fish resonate with the vortex
street
and it starts swimming upstream it's one
of the best examples ever
who do you give credit for that too
is that just evolution constantly just
figuring out by killing a lot of
generations of animals
uh like the most efficient motion is
that uh or maybe the
physics of our world completely like
it's like evolution applied not only to
animals but just the entirety of it
somehow
drives to efficiency like nature likes
efficiency
i don't know if that question even makes
any sense i understand the question
that's reason i mean
do they co-evolve yeah somehow yeah like
i don't know if an environment can
evolve but um
i mean there are experiments that people
do careful experiments that show that
um animals can adapt to unusual
situations and recover efficiency
so there seems like at least in one
direction i think
there is reason to believe that the
animal's motor system
and probably its mechanics adapt
in order to be more efficient but
efficiency isn't the only goal of course
sometimes it's too easy to think about
only efficiency but we have to do a lot
of other things
first not get eaten and then
all other things being equal try to save
energy by the way let's uh
draw a distinction between control and
mechanics like how
how can how would you define each yeah i
mean i think part of the point is that
we shouldn't draw a line as as clearly
as we tend to
but the you know on a robot we have
motors
and we have the links of the robot let's
say
if the motors are turned off the robot
has some passive dynamics
okay gravity does the work you can put
springs i would call that mechanics
right if we have springs and dampers
which our muscles are springs and
dampers and tendons
but then you have something that's doing
active work putting energy in
your motors on the robot the
controller's job is to
send commands to the motor that add new
energy into the system
right so the mechanics and control
interplay somewhere the divide is around
you know did you decide to send some
commands to your motor or did you just
leave the motors off and let them do
their work
would you say is most of nature
on the dynamic side or the control side
so like if you look at biological
systems if
you know we're living in a pandemic now
like do you think a virus is a
do you think it's a dynamic system or um
or is there a lot of control
intelligence i think it's both but i
think we
maybe have underestimated how important
the dynamics are
right um i mean even our bodies
the mechanics of our bodies certainly
with exercise they evolved but
so i actually i lost a finger in early
2000s
and it's my fifth metacarpal
it turns out you use that a lot in ways
you don't expect when you're opening
jars
even when i'm just walking around if i
bump it on something
there's a bone there that was used to
taking
contact my fourth metacarpal wasn't used
to taking contact it used to hurt
it still does a little bit but actually
my bone has remodeled
right over the lat over a couple years
the geometry the mechanics of that bone
change to address the new circumstances
so the idea that somehow
it's only our brain that's adapting or
evolving is not right
maybe sticking on evolution for a bit
because
it's tended to create some interesting
things uh
by peter walking
do you uh why the heck did evolution
give us
i think we're are we the only mammals
that walk on two feet
no i mean there's a bunch of animals
that do it
a bit there's a i think we are the most
successful bypass
i think some uh i think i read somewhere
that
um the reason the
you know evolution made us walk on two
feet is because uh there's an advantage
to being able to carry food back to the
tribe or something like that
so like you can carry it's kind of this
communal
cooperative thing so like to carry stuff
back
to um to a place of shelter and so on to
share with others um do you understand
at all the value
of uh walking on two feet from both a
robotics and a human perspective
yeah there are some great books written
about evolution of
walking evolution of the human body i
think it's
easy though to make bad evolutionary
arguments
sure most of them are probably bad but
what else can we do i mean i think um
a lot of what dominated our evolution
probably was not
the things that worked well sort of in
the steady state um
you know when things are when things are
good but but uh
for instance people talk about what we
should eat now because
our ancestors were meat eaters or or
whatever oh yeah i love that
yeah but probably you know the reason
that
one pre uh pre-homo sapien species
versus another
survived was not because of whether they
ate well
uh when there was lots of food but when
the ice age came
you know probably one of them happened
to be in the wrong place
one of them happened to forage a food
that was okay
even even when the glaciers came or
something like that i mean
there's a million variables that
contributed and we can't
and our actually the amount of
information we're working with and
telling these stories
these evolutionary stories is uh is very
little
so yeah just like you said it seems like
if we
if we study history it seems like
history turns on like these little
events
that uh that otherwise would seem
meaningless
but in the grant like when you in
retrospect
were turning points absolutely and that
that's probably how like somebody got
hit in the head with a rock
because somebody slept with the wrong
person back in the
cave days and somebody get angry and
that turned uh
you know warring tribes combined with
the environment
all those millions of things and the
meat eating
which i get a lot of criticism because i
i don't know um i don't know what your
dietary processes are like but
these days i been eating only meat
which is um there's a large community
people who say yeah probably make
evolutionary arguments and say you do a
great job there's
probably an even larger community of
people including my mom
who says it's deeply unhealthy it's
wrong but i just feel good doing it
but you're right these evolutionary
arguments can be flawed but is there
anything interesting to pull out for um
there's a great book by the way um look
a series of books by nicholas taleb
about fooled by randomness and black
swan um
highly recommend them but yeah they make
the point nicely that
probably it was a few
random events that yes maybe it was
someone getting hit by a rock as you say
uh that said do you think i don't know
how to ask this question or how to talk
about this but there's something elegant
and beautiful about moving on two feet
obviously biased because i'm human but
from a robotics perspective too you work
with robots on two feet
is it um is it all useful to build
robots that are on two feet as opposed
to four
is there something useful about it the
most um i mean the reason i
spent a long time working on bipedal
walking was because it was hard
and it was um it challenged control
theory in ways that i thought were
important
um i wouldn't have
ever tried to convince you that you
should
start a company around bipeds or
something like this
there are people that make pretty
compelling arguments right i think the
most compelling one
is that the world is built for the human
form
and if you want a robot to work in the
world we have today
then you know having a human form is a
pretty good way to go
there there are places that a biped can
go that would be hard for
other form factors to go even natural
places
but um you know at some point in the
long run
we'll be building our environments for
our robots probably and so maybe that
argument falls aside
so you famously run barefoot
do you still run barefoot i still run
barefoot that's so awesome
much to my wife's chagrin
do you want to make an evolutionary
argument for why running barefoot is
advantageous
um what have you learned about um
human and robot movement in general from
running barefoot
human or robot and or well you know it
happened the other way
right so i was studying walking robots
and
i was there's a great conference called
the dynamic walking
conference where it brings together both
the biomechanics community
and the walking robots community and so
i've been going to this for years and
hearing
talks by people who study barefoot
running and other the mechanics of
running
so i i did eventually read born to run
most people read born to run in the
first thing
right the other thing i had going for me
is actually that i
i wouldn't i wasn't a runner before and
i learned to run
after i had learned about barefoot
running i mean started running longer
distances
so i didn't have to unlearn and i'm
definitely
um i'm a big fan of it for me but i'm
not gonna
i tend to not try to convince other
people there's people who run
beautifully
with shoes on and that's good um
but here's why it makes sense for me um
it's all about the long-term game right
so i think it's just too easy to run 10
miles
feel pretty good and then you get home
at night and you realize
uh my knees hurt i did something wrong
right
um if you take your shoes off
then if you hit hard with your foot at
all
um then it hurts you don't like run 10
miles
and then and then realize you've done
something some damage you have immediate
feedback
telling you that you've done something
that's that's maybe sub-optimal and you
change your gait
i mean it's even subconscious if i right
now having run many
miles barefoot if i put a shoe on my
gate changes
in a way that i think is not as good um
so
so it makes me land softer and
i think my my goals for running are to
do it for as long as i can
into old age um not to win any
races and so for me this is a you know
a way to protect myself yeah i think um
first of all i've tried running barefoot
many years ago
uh probably the other way just just just
uh
reading born to run but
just to understand because i felt like i
couldn't
put in the miles that i wanted to and it
feels like
running for me and i think for a lot of
people
was one of those activities that we do
often and never really
try to learn to do correctly like it's
funny there's so many activities
we do every day like brushing our teeth
right i think a lot of us at least me
probably have never deeply studied how
to properly brush my teeth
right or wash as now with a pandemic or
how to properly wash our hands or do it
every day
but we haven't really studied like am i
doing this correctly but running felt
like one of those things
it was absurd not to study how to do
correctly because it's the source of so
much pain
and suffering like i hate running but i
do it
i do it because i hate it but it i feel
good afterwards
but i think it feels like you need to
learn how to do it properly so that's
where barefoot running came in and then
i quickly realized that
my gait was completely wrong i was
taking huge like steps
and landing hard on the heel all those
elements and so yeah from that i
actually learned to take
really small steps look i
already forgot the number but i feel
like it was 180 a minute or something
like that
and i remember i was uh i actually just
took songs that are 180 beats per minute
and then like tried to run at that beat
uh
just to teach myself it took took a long
time and i feel like uh
after a while you learn to run you
adjust it properly
without going all the way to barefoot
but i feel like barefoot is the legit
way to do it
i mean i think a lot of people would be
really curious about it
can you if they're interested in trying
what would you
how would you recommend a start or try
or
explore slowly that's the biggest thing
people do is they
are excellent runners and they're used
to running long distances or running
fast and they take their shoes off and
they
hurt themselves instantly trying to do
something that they were used to doing
i i think i lucked out in the sense that
i i couldn't
run very far when i first started trying
and i run with minimal shoes too i mean
i will
you know bring along a pair of actually
like aqua socks or something like this i
can just
slip on or running sandals i've tried
all of them
what's the difference between a minimal
shoe and nothing at all
what's like feeling wise what does it
feel like
there is i mean i noticed my gate
changing right
so um i mean your your foot
has as many muscles and sensors as your
hand does right
sensors ooh okay and we do amazing
things with our hands
and we stick our foot in a big solid
shoe right so there's
i think you know when you're barefoot
you're
you're just giving yourself more
proprioception and that's why you're
more aware of some of the gait
flaws and stuff like this now you have
less protection too
so um rocks and stuff i mean
yeah so so i think people are who are
afraid of barefoot running
they're worried about getting cuts or
getting stepping on rocks
first of all even if that was a concern
i think those are all like
uh very short-term you know if i get a
scratch or something it'll heal in a
week
if i blow out my knees i'm done running
forever so i will trade the short term
for the long term
anytime but even then you know this
again to my wife's chagrin um your feet
get tough
right and uh uh cows okay yeah i can run
over almost anything now
i mean what uh maybe can you talk about
is there tin like is there tips or
tricks that you have
uh suggestions about like if i wanted to
try it
you know there is a good book actually
uh there's probably more
good books since i read them but uh
ken bob barefoot ken bob saxton um
he's an interesting guy but i think his
book captured
uh the right way to describe running
barefoot running to somebody
better than any other i've seen
so you run pretty good distances
and you bike and is is there um
you know if we talk about bucket list
items is there something crazy on your
bucket list athletically that
you hope to do one day
i mean my commute is already a little
crazy um what are we talking about here
what what uh what distance are we
talking about well i live about 12 miles
from mit but you can find lots of
different ways to get there so i mean
i've run
there for a long many years a bike there
um blaze
yeah but normally i would try to run in
and then bike home
bike in run home but you have run there
and back before sure
barefoot yeah uh yeah or with minimal
shoes or whatever that
12 12 times two yeah okay
it became kind of a game of how can i
get to work i've rollerbladed i've
done all kinds of weird stuff but uh my
favorite one these days is i've been
taking the charles river to work
so i can put in a little row boat
not so far from my house but the charles
river takes a long way
to get to mit so i can spend a long time
getting there
and it's you know it's not about i don't
know it's just about
uh i've had people ask me how can you
justify taking that time
uh but for me it's just a magical time
to think to compress decompress
um you know especially i'll wake up do a
lot of work in the morning and then
i kind of have to just let that settle
before i i'm ready for all my meetings
and then
on the way home it's a great time to
load it sort of let that settle
so you you lead a like a a large
group of people i mean you're
is there days where you're like oh shit
i gotta get to work in an hour
like i i mean uh
is is there is there a tension there
where and like if we look at the grand
scheme of things just like you said long
term
that meeting probably doesn't matter
like you can always say
i'll just i'll run and let the meeting
happen how it happens
like what uh how do you
that zen how do you uh what do you do
with that tension
between the real world saying urgently
you need to be there
this is important everything is melting
down
how we're going to fix this robot
there's this uh
critical meeting and then there's this
the zen beauty of just
running the simplicity of it you along
with nature
what do you do with that i would say i'm
not a fast runner particularly
probably my fastest splits ever was when
i had to get to daycare on time because
they were going to charge me
you know some some dollar per minute
that i was late uh
i've run some fast splits to daycare
but that those times are passed now
i think work you can find a work-life
balance in that way i think you just
have to
i think i am better at work because i
take time to
think on the way in so i plan my day
around it
and i i rarely feel that those are
really in
at odds so what the bucket list item
if we're talking 12 times 2
or approaching a marathon uh
what uh have you run an ultra marathon
before do you do races is there what's
uh to win
i'm not gonna like take a dinghy across
the atlantic or something if that's what
you want but uh uh
but if someone does and wants to write a
book i would totally read it because i'm
a sucker for that kind of thing
no i do have some fun things that i will
try you know i like to
when i travel i almost always bike to
logan airport and fold up a little
folding bike on and then take it with me
and bike to wherever i'm going and
i've it's taken me or i'll take a
stand-up paddleboard these days on the
airplane and then i'll try to paddle
around where i'm going or whatever
and i've done some crazy things but um
but not for the
you know i've i now talk i don't know if
you know who david goggins is by any
chance
not well but yeah but i i talk to him
now every day so he's the person
who made me uh do this stupid challenge
so he he's insane and he does things for
the purpose
in in the best kind of way he does
things
like for the explicit purpose of
suffering
like he picks the thing that like
whatever he thinks he can do he does
more uh so is that do you have
that thing in you or you uh i think it's
become the
opposite it's uh so you're like that
dynamical system that
the walker the efficient uh yeah it's uh
leave no pain right you should end
feeling better than you started okay but
um it's mostly i think and kovit has
tested this because i've lost my commute
i think i'm perfectly happy walking
around uh
around town with my wife and uh kids if
they could get them to go
and it's more about just getting outside
and getting away from the keyboard for
some time just to let things compress
let's go into robotics a little bit what
to use the most beautiful idea in
robotics
whether we're talking about control or
whether we're talking about optimization
the math side of things
or the engineering side of things or the
philosophical side of things
i think i've been lucky to experience
something that
not so many roboticists have experienced
which is to hang out with
some really amazing control theorists
and uh
the clarity of thought that some of the
more mathematical control theory can
bring
to even very complex messy looking
problems
is really it really had a big impact on
me
and and uh i had a day even like
just a couple weeks ago where i had
spent the day on a zoom
robotics conference having great
conversations with lots of people
i felt really good about the ideas that
were flowing and
and the like and then i had a you know
late afternoon meeting with uh one of my
favorite control theorists and
um and we went from these
from these abstract discussions about
maybes and what-ifs and
and what a great idea to these super
precise
statements about systems that aren't
that much
more simple or or abstract than the ones
i care about
deeply and the contrast of that is
um i don't know it really gets me i
think
people underestimate um
maybe the power of clear thinking
and so for instance deep learning
is amazing um
i use it heavily in our work i think
it's changed the world
unquestionable it makes it easy to get
things
to work without thinking as critically
about it so i think one of the
challenges as an educator
is to think about how do we make sure
people get a taste
of the more rigorous thinking that i
think
goes along uh with with some different
approaches
yeah so that's really interesting so
understanding like the fundamentals the
first principles of the of the
the the problem where in this case is
mechanics
like how a thing moves
how thing behaves like all the forces
involved
like really getting a deep understanding
of that i mean from physics the first
principle thing
come from physics and here it's
literally physics
yeah and this applies in deep learning
this applies to um
not just i mean it applies so cleanly in
in robotics but
it also applies to just in any data set
i find this true i mean driving as well
there's a lot of folks in it that work
on autonomous vehicles
that don't study driving
like deeply i i might be coming a little
bit from the psychology side
but i remember i spent
a ridiculous number of hours at lunch
at this like lawn chair and i would sit
somewhere
somewhere on mit's campus there's a few
interesting intersections and we just
watched people cross
so we were studying um pedestrian
behavior
and i felt like as you record a lot of
video to try
and just the computer vision extracts
their movements how they move their head
and so on
but like every time i felt like i didn't
understand
enough i i just i felt like i wasn't
understanding what how are people
signaling to each other
what are they thinking how cognizant
are they of their fear of death
like what we like what's the game what's
the underlying game theory here what are
what are the
the the incentives and then i finally
found a live stream
uh of an intersection that's like high
def that i just i would
watch so i wouldn't have to sit out
there but that's interesting so like
that's tough that's a tough example
because i mean the learning humans are
involved
not just because human but i think um
the learning mantra is the basically the
statistics of the data will tell me
things i need to know right and
you know for the example you gave of all
the nuances of
um you know eye contact or hand gestures
or whatever that are happening
for these subtle interactions between
pedestrians and traffic
right maybe the data will tell us
they'll tell that story
i may be even i uh one level more
meta than than what you're saying
for a particular problem i think it
might be the case that data
should tell us the story but i think
there's a rigorous thinking
that is just an essential skill for a
mathematician or an engineer
that um i just don't want to lose it
yes there are there are certainly super
rigorous um
rigorous control oh sorry machine
learning people
i just think deep learning makes it so
easy
to do some things that um our next
generation
are um not immediately rewarded
for going through some of the more
rigorous approaches and i wonder where
that takes us
i just well i'm actually optimistic
about it i just want to
do my part to try to steer that rigorous
thinking
so there's like two questions i want to
ask
do you have sort of a good example
of rigorous thinking where it's easy to
get lazy
and not do the rigorous thinking and the
other question i have is like do you
have advice
of um how to practice rigorous
thinking and um you know in all the
computer science disciplines that we've
mentioned
yeah i mean there are times where
problems that can be solved with
well-known mature methods
could also be solved with with a deep
learning
approach and
there's an argument that you must use
learning even for the parts we already
think we know because if the human has
touched it
then you've if you've biased the system
and you've
suddenly put a bottleneck in there that
is your own mental model but
something like inverting a matrix you
know i i think we know how to do that
pretty well even if it's a pretty big
matrix and we understand that pretty
well and
you could train a deep network to do it
but you shouldn't probably
so so in that sense rigorous thinking is
uh
understanding the the scope and the
limitations of the mess
of the methods that we have like how to
use the tools
of mathematics properly yeah i think
you know taking a class on analysis
is all i'm sort of arguing is to take
take a chance to stop and
and force yourself to think rigorously
about even
you know the rational numbers or
something you know it doesn't have to be
the end-all problem but that exercise of
clear thinking i think uh
goes a long way and i just want to make
sure we we keep preaching don't lose it
yeah
but do you think uh when you're doing
like rigorous thinking or like maybe
uh trying to write down equations or
sort of explicitly like formally
describe a system
do you think we naturally simplify
things too much
is that a danger you run into like uh
in order to be able to understand
something about the system
mathematically
we uh make it too much of a toy example
but i think that's the good stuff right
um that's how you understand the
fundamentals
i think so i think maybe even that's a
key to intelligence or something but
i mean okay what if newton and galileo
had deep learning
and and they had done a bunch of
experiments
and they told the world here's your
weights of your neural network i've
we've solved the problem
yeah you know where would we be today i
don't i don't think we'd be as far
as we as we are there's something to be
said about having a the simplest
explanation
for a phenomenon so i don't doubt that
we can train neural networks to predict
even
physical you know
f equals m a type equations
but um i maybe
i want another newton to come along
because i think there's more to do in
terms of
coming up with the simple models for
more complicated tasks yeah uh
let's not offend the ai systems from 50
years from
now that are listening to this that are
probably better at
might be better coming up with f equals
m a equations themselves
so sorry i actually think um learning is
probably a route
to achieving this but the representation
matters
right and i think having
a function that takes my inputs to
outputs
that is arbitrarily complex may not be
the end
goal i think there's still you know the
most
simple or parsimonious explanation for
the data
simple doesn't mean low dimensional
that's one thing i think that we've
a lesson that we've learned so you know
a standard way to do
model reduction or system identification
and controls is to
the typical formulation is that you try
to find the minimal state
dimension realization of a system that
hits some error bounds or something like
that and that's maybe not
i think we're we're learning that that
was that the
state dimension is not the right metric
of complexity of complexity but for me i
think a lot about contact
the mechanics of contact the robot hand
is picking up an object or something
and when i write down the equations of
motion for that they're they look
incredibly complex not because
actually not so much because of the
dynamics of the hand when it's moving
but it's just the interactions and when
they turn on and off
right so having a high dimensional you
know but
simple description of what's happening
out here is fine but if when i actually
start touching
i write down a different dynamical
system for every
polygon on my robot hand and every
polygon on the
object whether it's in contact or not
with all the combinatorics that explodes
there
then that's too complex so i need to
somehow summarize that with a
more intuitive physics
way of thinking and yeah i'm very
optimistic that machine learning will
get us there
first of all i mean i'll probably do it
in the introduction but you're
one of the great robotics people at mit
you're a professor at mit
you've teach them a lot of amazing
courses you
run a large group and you have a
important history for mit i think as
being a part of the darpa robotics
challenge
can you maybe first say what is the dark
robotics challenge and then
tell your story around it your journey
with it yeah sure um
so the darpa robotics challenge it came
on the tales of the darpa
grand challenge and darpa urban
challenge which were the
challenges that brought us put a
spotlight on self-driving
cars
guild pratt was at darpa and
pitched a new challenge that involved
disaster response
it didn't explicitly require humanoids
although humanoids came into the picture
this happened shortly after the
fukushima disaster
in japan and our challenge was motivated
roughly by that
because that was a case where if we had
had robots that were ready to be sent in
there's a chance that we could have
averted disaster
and certainly after the um in the
disaster response
there were times we would love we would
have loved to have sent robots in
so in practice what we ended up with was
a
grand challenge a darpa robotics
challenge
where boston dynamics was
was to make humanoid robots people like
me
and the the amazing team at mit
were competing first in a simulation
challenge
to try to be one of the ones that wins
the right to work on
one of the uh the boston dynamics
humanoids in order to compete in
the the final challenge which was a
physical challenge
and at that point it was already so it
was decided as humanoid robots
there were there were two tracks there
you could enter as a hardware team where
you brought your own robot
or you could enter through the virtual
robotics challenge as a software team
that would try to win the right to use
one of the boston dynamics robots which
are called
atlas atlas humanoid robots yeah it was
a 400-pound
marvel but a you know pretty big scary
looking
robot expensive too expensive at the
time yeah
okay so uh i mean how did you feel
at the prospect of this kind of
challenge i mean it seems
you know autonomous vehicles yeah i
guess that sounds hard
but uh not really from a robotics
perspective it's like
didn't they do in the 80s is the kind of
feeling i would have
uh like when you first look at the
problem it's on wheels
but like humanoid robots
that sounds really hard
so what like what are your the
psychologically speaking what were you
feeling excited
scared why the heck did you get yourself
involved in this kind of
messy challenge we didn't really know
for sure
what we were signing up for in the sense
that you could have something that
as it was described in the call for
participation
that could have put a huge emphasis on
the dynamics of walking
and not falling down and walking over
rough terrain or the same description
because the robot had to go into this
disaster area and
turn valves and and pick up a drill
cut the hole through a wall it had to do
some interesting things
the challenge could have really
highlighted perception and
autonomous planning or it ended up
that you know locomoting over a complex
terrain played a pretty big role in the
competition
so and the degree of autonomy wasn't
clear
the decree of autonomy was always a
central part of the discussion
so um what wasn't clear was how we would
be able how far we'd be able to get with
it
so the idea was always that you want
semi-autonomy
that you want the robot to have enough
compute that you can have a degraded
network link to a human and so the same
way you we had degraded networks
at many natural disasters you'd send
your robot in
you'd be able to get a few bits back and
forth but you don't get to have enough
potentially to fully
uh operate the robot in every joint of
the robot
so and then the question was and the
gamesmanship of the
organizers was to figure out what we're
capable of push us as far as we could
so that um it would differentiate the
teams that
put more autonomy on the robot and had a
few clicks and just said go there do
this go there do this versus someone
who's picking
every footstep or something like that so
what were some memories
painful triumphant from the experience
like what was that journey maybe
if you can dig in a little deeper maybe
even on the technical side and the team
side that that whole process of um
from the early idea stages to actually
competing
i mean this was a defining experience
for me i i
it was it came at the right time for me
in my career i had gotten tenure before
i was
do a sabbatical and most people do
something you know
relaxing and restorative for a
sabbatical so you got tenure before the
the before this yeah yeah yeah it was a
good time for me
i had i had we had a bunch of algorithms
that we were very happy with we wanted
to see how far we could push them and
this was a chance to really test our
metal
to do more proper software engineering
the team we all just worked our butts
off
we you know we're in that lab almost all
the time
okay so i mean there were some of course
high highs and low lows
throughout that anytime you're you know
not sleeping and
devoting your life to a 400 pound
humanoid um
i remember actually one funny moment
where we're all super tired and
so atlas had to walk across cinder
blocks that was one of the obstacles
and i remember atlas was powered down
and hanging limp you know on the on its
harness
and the the humans were there like
laying you know picking up and laying
the brick down so that the robot could
walk over it and i thought what is wrong
with this you know we've got a robot
just watching us do all the manual labor
so that it can take its little
um stroll across the train but
i mean even the even the virtual
robotics challenge was was
super nerve-wracking and dramatic i
remember
um so so we were using gazebo as a
simulator
uh on the cloud there was all these
interesting challenges i think
um the investment that that osrs
fc whatever they were called at that
time brian gerkey's team at open source
robotics
um they were pushing on the capabilities
of gazebo in order to scale it to the
complexity
of these challenges so um
you know up to the virtual competition
so the virtual competition
was you will sign on at a certain time
and we'll have a network connection to
another
machine on the cloud that is running the
simulator of your robot
and your controller will run on this
this controller this computer and and
the physics will run on the other and
you have to connect
now um the physics they wanted it to run
at real-time rates
because there was an element of human
interaction um and humans
could if you do want to tell the op it
works way better if it's at
frame rate oh cool but it was very hard
to simulate these
comple these complex scenes at real-time
rate
so right up to like days before the
competition
the the simulator wasn't quite
at real time rate and that was great for
me because my controller was solving a
big pretty big optimization problem
and it wasn't quite at real-time rate so
i was fine i was keeping up with the
simulator we were both running at about
0.7
and i remember getting this email and by
the way the perception
folks on our team hated that that they
knew that if my controller was too slow
the robot was going to fall down and and
you know no matter how good their
perception system was if i can't make my
controller fast
anyways we get this email like three
days before the virtual competition well
you know it's for all the marbles we're
going to either get a humanoid robot
or we're not and we get an email saying
good news
we made the robot does the simulator
faster it's now one point
and uh yeah we're i was just like oh man
what are we going to do here so
yeah that came in late at night for me
um a few days ahead a few days ahead
i went over there was it happened that
frank permentor who's a
a very very sharp he's a he was a
student at the time
working on optimization was he was still
in lab
uh frank we need to make this quadratic
programming solver faster
not like a little faster it's actually
you know um
and we wrote a new solver for that qp
together that night
and you start terrifying so there's a
really hard optimization problem
that you're constantly solving you
didn't make the optimization problem
simpler
you you wrote any solver so um i mean
your observation is almost spot on well
what we
did was what everybody i mean people
know how to do this but we had not yet
done
this idea of warm starting so we are
solving a big optimization problem
at every time step but if you're running
fast enough the optimization problem
you're solving on the last
time step is pretty similar to the
optimization you're going to solve with
the next
we had course had told our commercial
solver to use warm starting
but even the interface to that
commercial solver
was causing us these delays so what we
did
was we basically wrote we called it
fastqp at the time
we wrote a very lightweight very fast
layer
which would basically check if nearby
solutions to the quadratic program
were which were very easily checked uh
could stabilize the robot
and if they couldn't we would fall back
to the solver you couldn't really test
this well right
um or like i mean so we always knew that
if we
fell back if we it got to the point
where if for some reason
things slowed down and we fell back to
the original solver the robot would
actually literally fall down
um so it was it was a harrowing
sort of edge we're ledge we were sort of
on but
i mean actually like the the 400 pound
humor could come crashing to the ground
if you if you
if your solver is not fast enough but
you know that we have lots of good
experiences
so can i ask you a weird question i
i get um about idea of hard work
so um actually people
like students of yours that i've
interacted with
and just and robotics people in general
but they uh they have
moments at moments have worked harder
than
uh most people i know in terms of if you
look at different disciplines of how
hard people work
but they're also like the happiest like
just like
i don't know um it's the same thing with
like running people that push themselves
to like the limit
they all also seem to be like the most
like full of life somehow
uh and i get often criticized like
you're not getting enough sleep what are
you doing to your body
blah blah blah like this kind of stuff
and
i usually just kind of respond like i'm
i'm doing what i
love i'm passionate about i love it i
feel like it's
it's invigorating i actually think i
don't think the lack of sleep
is what hurts you i think what hurts you
is uh stress and lack of doing things
that you're passionate about
but in this world yeah i mean can you
comment about
uh why the heck robotics people
are uh
willing to push themselves to that
degree is there value in that
and why are they so happy i think
i think you got it right i mean i think
the causality is not
that we work hard and i think other
disciplines work very hard too but it's
i don't think it's
that we work hard and therefore we are
happy
i think we found something that we're
truly passionate about
it makes us very happy and then we
get a little involved with it and spend
a lot of time on it um
what a luxury to have something that you
want to spend all your time on
right we could talk about this for many
hours but
maybe if we could pick is there
something on the technical side on the
approach
you took that's interesting that turned
out to be a terrible failure or a
success that you carry into your work
today
about all the different ideas that were
involve