Nick Ouellette: What flocks of birds can tell us about engineering

March 9, 2020 0 By Kody Olson

(upbeat music playing) – [Russ Altman] Today on
the future of everything, the future of flocking and swarming. Now, anyone who has ever seen
a flock of birds in flight has likely been impressed with the beauty and the coordination of
the birds as they move, they turn in the air,
they do these maneuvers that are just quite spectacular. And we all look at this
and I think we all say, How does that happen? How are they dividing and then rejoining, how are they making turns? Is there a head bird, as it were. Is there a head bird making all the calls, or did they in some way watch
all the birds around them and take cues from them, is there a plan, or is
this totally spontaneous. Now I have always assumed that
the positions of the birds are determined at least in
part by what I would think of as optimal aerodynamics. If you’ve ever been on a bicycle, you know that if you get behind somebody who’s pushing the air out of the way, it is a lot easier to cycle than if you’re having to be the one in the front. And so I assume that the
birds position themselves in a way that is in some
sense aerodymically optimal. I actually have no idea if that’s true but I’m hoping to learn about that. Do the birds take turns at the front, in order to distribute the responsibility both for leadership, like
for where we’re going, but also energy expenditure. I think the same questions
might apply to schools of fish or swarms of insects. I think the details are
probably very different, but the sense of wonder in watching them and seeing this amazing coordination of individuals is similar. In addition to the
beauty of this phenomena, they also have practical utility. For example, will self-driving
cars in the future fly in formation? Will they look more like
birds, fish, insects, or maybe a herd of horses? Nick Willette is a professor
of civil and environmental engineering at Stanford University. Nick studies the physics,
energetics and structure of flocks and swarms,
and related phenomena. Nick, why would a civil
engineer study these phenomena? We might expect it to occur
in a biology department. And what have you learned
that may be useful in a context of engineering new systems? – Yeah, you know, I get
that question a lot. The fully honest answer – This is what we’re searching for on The Future of Everything. – I study these things
because they’re beautiful. Because they’re ubiquitous,
you see them all the time. And it’s one of- A lot of
what motivates my research is, you go out side, you look around you, you see something that’s interesting, you think to yourself,
Gee, someone probably knows why this happens. And more often than not, when
you do a little but of reading you find out that that’s not the case. That you only have to scratch the surface before you get to some
kinds of what seems like basic questions, where nobody
really knows the answer. So that’s the real, full,
honest answer as to why I’m interested in these
kinds of phenomena. – And your colleagues in
engineering are OK with it? – My colleagues in
engineering are wonderful. And in part, I think that’s
because it’s very very difficult in general to predict you know,
twenty years down the line, what basic research now is
going to lead to something really interesting in the future. That being said, I think
there are compelling reasons why one might want to look
at these kinds of phenomena from the standpoint of engineering. And it’s part of a broader
move over the past few decades toward bio-inspired
engineering more generally, that you look to the natural
world to see how evolution has solved problems, and if
the same or similar problems show up in whatever you want to design, at least it’s reasonable
to ask the question as how nature has done this. – That’s totally fair. So let me ask you, when
you look at these flocks in their beautiful formations, what are the problems
you see them solving? – And that is actually in some ways the most difficult
question that we’ve found to address in all of this work. Because at the end of the day, you cannot go and ask the birds So why you doin’ this? What’s the purpose? You can make fairly
reasonable arguments based on intuition from ecology, so
interfacing with ecologists and biologists is really important here. In some contexts- so I
should say, I should back up just a smidge and say that one of the hints that collective behavior, as this broad field is known, may be really valuable from
an engineering standpoint is that you see this at every
single scale in biology, That individual units or
organisms work together to solve problems. Everything from single celled
organisms like bacteria, like cells, all the way up to whales. So you have literally the
entire spectrum of biology that all cooperates to accomplish things. – And there is an idea that many of these are distributed in the sense that there is not a central boss. – Right. – And then that leads to the question that how could you do that? Because so many human
systems are hierarchal and do have a center but not all human systems are like that. – But not all human systems. And in particular, not in the systems that evolution has designed. So humans are much like
birds or fish or insects in that we have collective
crowding behavior all the time. So in that especially
kicks in when something is out of the ordainary enough that it shuts down our
primary cognitive functions. So if there’s an emergency,
if there’s a disaster, and you’re in a big crowded situation, I don’t think any of us,
if you think about it, you don’t make rational decisions. You don’t carefully weigh all the options- should I put my left foot here, should I put my right foot there, should I go in which direction. You follow the crowd to get
away as quickly as possible- you think- from whatever is going on. So there are reasons to
think that the kind of- and this gets back to the question of why would a civil
engineer want to do this- there’s good reason to think
that things that we learn about how collective groups behave and how they can be manipulated may be able to valuably
mapped onto questions about crowd control, about
the design of public spaces to avoid instabilities
of crowding behavior that leads to events like
trampling or dangerous situations. – Great, so before before we get to those engineering applications, I do want to go back to the
birds, because I do really actually want to ask you the
questions to these questions that I raised. So in fact, is there a head
bird, and how do they do the leadership of these flocks? – So the first thing
to distinguish there – because the answer to everything
is always this complicated- there are really two kinds of flocks you want to distinguish. And then we all have seen these. – Good, we’re gonna have
a taxonomy of flocks. – Right, the first kind,
which kind of looks like it has a leader though it probably doesn’t and where you may see aerodynamic benefits are the kind of V
formations of flocks you see in large migratory birds. Geese, storks, ibis, all
these kinds of things. – Very beautiful V shaped with
sub-Vs, like fractal with Vs. – Yeah. So that’s not what
we have worked on so much. I know that literature
anecdotally, but I haven’t worked on that myself. – In general, are they
aerodynamically pretty good? – Yes, although it’s complicated. So everybody wants to make the analogy to bikers. – Bikers, that’s one I did myself. – Or trucks on the highway,
so trucks will do the same kind of thing. In fact our dean- one of the
most recent papers I published on that asked me that very question. With cycling with as a you
know kind of touchstone. The difference really
comes into the fact about how the birds are moving. And what’s easy to forget is that birds don’t just keep their wings
fixed and glide, they flap. And so the way aerodynamic
drag works on a flapping wing as opposed to a fixed
wing is very different. So you can get aerodynamic
savings, in fact it’s been shown that these birds
do get aerodynamic savings. But the key thing there
is actually the phase of the wing beats down the V chain. So you have to catch the updraft – Oh, that’s a beautiful thing. – From the bird in front of you and then you get a boost from it But if you’re flapping at the wrong time then you want to go up and the vortex shed from the bird in front
of you is going down and then it’s bad for you. – Right. So then this
gonna be slightly different principles than the Blue Angels use because they’re all fixed wing. – Right. They’re all
fixed wing, and so drag works differently. – This is The Future of
Everything. I’m Russ Altman. I’m speaking with Nick Willett about- Well, the bird taxonomy
we just learned about Vs, but there’s another
important type of flock. – So now think about the
last time you went to a city and saw a bunch of pigeons flying around. Pigeons will do this, most
birds, songbirds will do this, starlings are the classic
example that form massive flocks. In those kinds of
situations, the flock itself is not as rigidly sort
of constructed as a V. The bird position is sort of more random. What we and others have found
in those kinds of flocks is that in fact it’s aerodynamically bad, in that the birds wind
up expending more energy to participate in a flock
than they would if they were flying on their own. – And they do look somewhat
chaotic, just on a visual, even though they’re
beautiful and coordinated, they seem to be making
tighter turns and vortices and things like that that
look like they might in fact be more energetically expensive. – Yeah, and that is borne
out by the data as well. – And those are the ones that you study. – Those are the ones that we study. – Paint me a picture now for
how the laboratory looked. What does it look like? What are the key tools that you guys use to make these studies? – So the first thing is-
– It must be cool technology. – Yeah. And fact, the technology
is how I got into this in the first place. So the first thing to note in this front is that it’s not in the laboratory. So Stanford is a wealthy university. They give you nice lab space,
all these kinds of things when you come. They don’t give you enough lab space to have a few thousand birds Flying around in free space. So this is very much a field project. So I have a wonderful
collaborator in England in Cornwall who has been studying the native jackdaw populations. The jackdaw are a small
crow species, very social. – And I’ve heard that
crows are very smart. – Crows are VERY smart! – Which might confound your science. But we’ll get to that later. (laughing) – People are nominally smart
too, right, so that’s – – Well put! – And that’s actually an
interesting thing to ask about how does intelligence map on to this ubiquitous biological phenomenon, where animals and organisms
that are not very smart do things that look similar
to animals that we consider to be very smart. So this is not a project
that is done in a laboratory, it’s a project that’s done outside. That’s part of the reason
why we haven’t focused on the V formation flocks. So the technology that we use here is in principle fairly straightforward. We just use camera imaging to watch where the birds are going. So the simplest kind of thing you would do is you go and take a camera,
you point it at the sky, you see a bird flock flying around and you take some pictures of it. – And it would be a movie. – It’d be a movie. – But that’s 2-D. – That’s 2-D. And there’s only so much you can tell from a 2 dimensional projection
of what the birds are doing. So what we actually want to
do is to measure them in 3-d. We want to be able to locate
in 3 dimensional space where all the birds
are, how they’re moving, and as much other detail as we can get. So the way we accomplish this
is similar to the way we see in 3 dimensions all the time which is to use more
than one imaging device. So we have 2 eyes, and that allows us, with some neural
processing, to reconstruct a picture of the 3-d world. We do the same thing
with multiple cameras. – So these flocks, I
presume they are absolutely freely behaving, behaving,
there’s no training. – There’s no training. – And you don’t physically
even limit them? – Nope. – So it’s catch as
catch can in some sense. – Yes, and this is why
having a collaborator who has spent decades mapping out the behavior of these birds is vital to this project. Because the first thing you learn when you go to do field work
to try to look at the sky to see birds is that there’s a lot of sky, and birds are very small. So if you just randomly pick a
spot and put some cameras out the chances of seeing a good
bird flock flying over that is zero. – This is The Future of Everything. I’m Russ Altman, I’m
speaking with Nick Willett. Now about studying birds in
the wild with 3-d capabilities. What do we learn? I mean I’m
sure people have been dying to hear. Where is the science now
in terms of understanding the coordination and
distributed decision making of these flocks? – There’s a number of things that people have learned about this. The first large-scale experiments, quantitative of measuring
birds were with starling flocks from a group in Rome. They found a number of
very interesting things. So there’s been a supposition in the field for a long time that
it’s reasonable to expect that if you’re a bird in a flock, and it’s a dense flock, and
there’s thousands of birds, there’s no way that you know
what everybody else is doing. There’s not a chance. Which means that all of the
coordination that you see has to come out of- The decisions you as an
individual make based on information from your local neighborhood. But one of the questions is
what defines that neighborhood? Is it that there’s a distance
in space that you can see? 5 meters? You just look at everyone there? – These are the questions that as I was writing my introduction
I said I have no idea what the answer to these questions are. – The other way that you
could think of defining what is a neighborhood mean
is that you pay attention to some number of other birds And it doesn’t really
matter if they’re 5 meters, ten meters, 2 meters away
from you, you pick, say, 8, and then you follow that motion. There’s good reason to think
that that’s biologically more reasonable, because
you don’t get then overloaded if the flock gets denser. And in fact with the starlings,
that’s what was found. – And so how do you prove
something like that? – It’s a very difficult- – So you have a model that,
okay, the bird is either looking at one or two
birds in front of him, or an assembly of birds around them. I guess that leads to
specifically testable hypotheses? – Yes! So the way we do this
is to make the hypothesis that if reliably you are
paying attention to other birds at some distance away from
you, either whether that being a counting distance or a distance in space there’s probably gonna
be some spots you’d like to position yourself
relative to those others that are preferable. You want to be able to keep
them in view, maybe you want the aerodynamics to be not terrible. So there’s gonna be some statistical bias. So what you do here to
get an estimate of range you see how far away do
I have to push that range away from me before the
statistics look uniform in space. – Yes. So that’s good, and so then
that allows you to conclude that there’s like a set of birds around, maybe not even the few closest, but they’re a little more
complicated than that. You made a vague reference
to this a moment ago. Is there also an awareness of
the I guess the aerodynamic, the pressure, the pressure
environment around the bird, like the aerodynamics, I’m
sensing turbulence here, I’m sensing smooth air over there, or is there no evidence for that? – Honestly we don’t
know, because we can now, you gotta imagine that the
birds when you got a camera on the ground, you’re looking
at a flock in the air. So it’s very far away from you. So at this point we can measure
what the birds are doing, but we don’t have a local
measurement of the fluid flow around them. My guess is that the
answer is probably no. That they don’t pay that much
attention to it on average because the statistics you
see don’t seem to matter sort of where you are in the flock, if you’re at the front,
if you’re at the back, at if you’re on the sides. The fluid mechanics
environment will be different in all those cases. – Yes, that makes sense. – So if the aerodynamics is a player, it does not appear to be
a primary player in this. – So I know that a part of
your work involves simulation. So you go back to the
lab, to the regular lab, not the beautiful Cornwall, you know I’m going into a reverie thinking about what it
must be like out there. – Well it’s December. That’s when they do
what we want them to do. – Oh, okay, I’m updating my reverie! But let me ask when you
get back to the lab, what kind of simulations are you doing, and how does that inform
what you do next time you’re in the field? So the simulations are a lovely
place to test hypothesis. So you can build a little model that says okay suppose we think
that a bird pays attention to seven or eight of its neighbors or it pays attention to
everything in some distance. You can put those rules into a computer and simulate what you would get and then try to look in
those two simulations where you know what you put in. You never know with the birds, you don’t know what they’re doing. But you know exactly what
you put into the computer and then you can see what
the output looks like. – And if it matches the behaviors- So that actually- so this is
kind of a random question. Has the cinema industry
approached you about getting better fidelity CGI
simulations of bird flocks? – So they haven’t approached
me because this has been done in the cinema since the 80s. – Oh, so they’re pretty
clueful about birds? – Mmm hmmm. So actually one
of the real seminal papers in this field was written
for the computer science SIGRAFF conference in
1987 by a wonderful person who she actually lives in
Mountain View just down the road. So it’s a classic paper and it’s been used in actual feature films
since the early ’90s if not before, and in the
video industry as well. – Now are those things of
interest to you, or are they in some way cheating in a way
that it doesn’t give you the insight that you’d like? – It’s not cheating, but I will
say that we haven’t focused on it too much. Because one of the things
that you start to learn when you do lots of different simulations is that many, many different sets of rules give you a visual output
that looks very reasonable. – So they may have set upon
something that gives you a perfectly good looking
movie, but not related to the actual mechanisms
used by the birds. – Right. And this gets back
to the engineering context in which I’m working.
If at the end of the day I have learned what the birds are doing and then potentially apply
this to an engineering problem and say “Evolution means
that this is probably good,” if I understand what
it’s being optimized for, I need to be pretty sure
that I got it right. – A perfect segue to our next segment. This is The Future of Everything. This is I’m Russ Altman. More with Nick Willett about birds, but now the engineering
implications of all these learnings next on Siris XM. – Welcome back to The
Future of Everything. I’m Russ Altman, I’m
speaking with Nick Willett about swarming, flocking. We’ve been talking
about the study of birds and their flocking capabilities
but we promised to get back to the engineering
applications of these ideas. So Nick, paint a picture for
me about how some of these learnings are either
directly useful, or leading to useful information. – There’s a couple- I should
preface this with I haven’t- we’re still sort of in the discovery phase of this kind of research. So I haven’t personally
spent a lot of time on the applications side. But two areas that I think are
probably the most promising to apply this kind of work in engineering. One is on the question of human
crowds, either crowd control or the design of spaces
to manipulate crowds in a passive way. And on the control of distributed
systems more generally. So if you take the second
of those for example, more and more in- – And define distributed
systems for people who might not think about them every day. – So in some sense a traditional
way of doing engineering if you think about how
you control something you build a system that’s sort
of one big monolithic thing. So take the powering, one of
the other things that we work on in the lab is questions
about how you might want to design next generation power systems or electricity systems for cities. So in the standard old design is you build one big power plant and it
pipes all the electricity to the city and you’re fine. Well these days, with the development of lots of local renewables,
you could do that still, or you could put a solar
panel on everybody’s roof, or you could do anything in between. So those would be examples
of distributed systems, where you have many, many, many components to the system that all need to interact. But as an engineer you still
need to have that system be controlled. It should do what you want it to do, it shouldn’t fail, it should be robust, all these kinds of nice things. Traditional engineering
control work is a very top-down kind of thing: you want to know what is the total information in the system, what is everything doing,
and then make decisions based on that. As we were just arguing, the
birds or animals don’t do that. A single bird doesn’t know
what the other birds are doing. And yet the flock itself
is very coherent and very consistent in its behavior. So this suggests that there’s
an alternative paradigm where you use only local information with local interactions
that are of the right type such that the entire system
still has functionality and is very very robust. – Got you. – And I would argue that that kind of bottom-up control scheme should be at least be on the table. As engineers we move more and
more toward thinking about distributed systems rather
than monolithic systems. – And are you thinking
about distributed systems like self-driving cars and trucks – Absolutely! or from your perspective, are they all about the same? Well, that’s a good question. I would say there are aspects
to all of these these things that are about the same. Once you- and this goes
back to your question about what do you learn about putting
on the computer in a model- In some sense, once you have
abstracted the real system into a model and you’ve
validated the model, well now it’s just math. And anything you can apply that math to, so any different mapping, you
have a variable in your model and you know it came from meeting a bird, and now it means a car, doesn’t really matter
from the math standpoint. – Now, but let me ask,
because you’ve mentioned 2 things have come up in our conversation: Humans and smart crows. And they have social structures. So does that matter? – That I think is actually a
very very interesting thing. And this is where a lot of the recent work we’ve been doing with animals where we’ve been focusing. So the answer to that question even a couple of years ago was not known. So you can definitely say that humans have certain social interactions. Does that matter in a crowd situation? One of the reasons I was
excited to work on jackdaws is that unlike what we
think about starlings- the biology is always difficult- we know that jackdaws
and other crow species have very intricate social systems. And for jackdaws in particular we know that they mate for life. So you have a society that’s
built of these mated pairs. In the roosting season, in
the winter months in England where there’s no young in the nest, both members of that pair are
free to fly around all day. So when they form these flocks, anecdotally people have seen these and said it look like
that flock is composed of lots of little pairs of birds. – And you can see the pair
behavior in the flock? – You can see the pair
behavior in the flock. And we can pick that out automatically. So once we get our data set,
we’ve imaged the flocks in 3d we know where all the birds are, you can actually pick out
which ones are paired together. – And it’s something like these two maintain a close distance
over a long period of time- – Over a long flight- – Which allows us to infer
that they are spouses. I don’t know if that’s the right word. – Partners. – Partners, thank you. And they also maintain similar
configurations over time so that the placement of each
bird relative to each other is also fairly consistent. So there’s a lot of statistical
measures we can throw at this to determine what those pairs are. And then you can start
to ask the question, okay great you found
pairs. Does it matter from the stand point of the flock that there is structure on the inside? And the answer, in some sense
surprising answer to that is, yes it does! And what we found is that
the more pairs you have in the flock as a percentage
of the number of birds – Because not all the birds- – There are some bachelors- – There’re some singles, – Bachelorettes, whatever,
forgive me everybody. – The more pairs you
have, the less responsive the whole flock is to perturbations
from the outside world, things like predators. – This The Future of Everything. This is Russ Altman, I’m
speaking with Nick Willett, and we’ve just learned that
the mating pairs in this case of these birds actually affects
the dynamics of the flocks. So please! – So the more pairs you
have, the overall flock is sort of not as effective
at doing things like avoiding predators as
it would be otherwise. – So it’s a little bit of a negative? – Little bit of a negative,
for the society, for the group. But at the individual
level, that is balanced by a couple of interesting savings. What we’ve also found
is, so I’ve told you okay the birds pay attention to
some number of neighbors. Well that number is smaller
if you’re part of a pair versus if you’re not. – You’re focused on your kin. – Well it’s typically about 3, 3 or 4. So definitely your partner,
and then a couple of others close to you. But about half the range,
half the number of birds you pay attention to if
you’re not part of a pair. And that has an implication
back to the aerodynanics. So what we found is that
it’s always an energetic hit. There’s an energetic cost
to being part of the flock. Which is reasonable to
pay if you get benefits like a hawk comes by and
eats one of your neighbors instead of you. But that cost is
mitigated at a local level if you’re part of a pair. You’re not paying
attention to as many birds, so it’s more beneficial
for you, so there’s an individual level savings
but a global cost to the group. – And it’s not hard for me
to imagine similar dynanics in a crowd fleeing an
emergency where your partner, you’re keeping an eye on them,
you are trying to save then if they’re in a tough spot
where otherwise nobody might try to save them,
but that might lead to a less effective
emptying of the theater. – Or at least something
you need to know about when you start to try
to poke and prod at that and manipulate it. The other area where I think this might be interesting to think if you think about self-driving car fleets and controlling the with
these kinds of local rules Well you got your Google cars, and you got your Uber cars, and you got all these
other kinds of things. And even if on paper, they’re
supposed to be communicating in the same way, protocols
may be slightly different, there may be asymmetries. – Right – And what we’ve been finding in the birds is that those little local asymmetries can have consequences. – So now we have a potential- I’m not sure it’s an
engineering principle yet- but you’re pushing close to a principle that we may want to evaluate
the costs and benefits of having different algorithms
on the different cars, because that may lead
to a similar behavior as birds that are caring more about some birds than other birds. – Or at least it’s something
that one should be aware of As we move towards using
these kinds of rules that we’re learning from
nature and applying them in engineering contexts. – So when will these principles affect people in the real world? When are we going- and I
know it always takes time. – Always takes time. – Give me a sequence of
events that might lead to these principles affecting the systems that are being built. – That’s a question I
probably can’t answer. I don’t know that I want
to speculate too much. – Please do, we’re in
the last thirty seconds. – Yeah, if I had to
guess, I would guess that it’s gonna be in the crowd control arena that you’re first going
to see things like this. ‘Cause that’s being, that’s
a longer, because we’ve known about crowds a lot longer
than self-driving cars. – So human crowds. – Human crowds, I would
guess that there’s gonna be- – And perhaps the way
that they set up exits, the way that they engineer
buildings for entrance and exit. – This is already something
people are thinking about as we get more data, I think
we’ll things happening there. – And that’s actually exciting
for improved public safety. – Absolutely. – There are cities,
the cities are crowded. Fantastic. Thanks for listening to
The Future of Everything. I’m Russ Altman. If you missed any of this
episode, listen any time on demand with the Sirius XM app.