-
Over a million people are killed
each year in disasters.
-
Two and a half million people
will be permanently disabled or displaced,
-
and the communities will take
20 to 30 years to recover
-
and billions of economic losses.
-
If you can reduce
the initial response by one day,
-
you can reduce the overall recovery
-
by a thousand days, or three years.
-
See how that works?
-
If the initial responders
can get in, save lives,
-
mitigate whatever flooding
danger there is,
-
that means the other groups can get in
-
to restore the water,
the roads, the electricity,
-
which means then the construction people,
the insurance agents,
-
all of them can get in
to rebuild the houses,
-
which then means you
can restore the economy,
-
and maybe even make it better
and more resilient to the next disaster.
-
A major insurance company told me
-
that if they can get a homeowner's claim
processed one day earlier,
-
it'll make a difference of six months
-
in that person getting
their home repaired.
-
And that's why I do disaster robotics --
-
because robots can
make a disaster go away faster.
-
Now, you've already seen
a couple of these.
-
These are the UAVs.
-
These are two types of UAVs:
-
a rotorcraft, or hummingbird;
-
a fixed-wing, a hawk.
-
And they're used
extensively since 2005 --
-
Hurricane Katrina.
-
Let me show you how this hummingbird,
this rotorcraft, works.
-
Fantastic for structural engineers.
-
Being able to see damage from angles you
can't get from binoculars on the ground
-
or from a satellite image,
-
or anything flying at a higher angle.
-
But it's not just structural engineers
and insurance people who need this.
-
You've got things like
this fixed-wing, this hawk.
-
Now, this hawk can be used
for geospatial surveys.
-
That's where you're
pulling imagery together
-
and getting 3D reconstruction.
-
We used both of these at the Oso mudslides
up in Washington state
-
because the big problem was
-
geospatial and hydrological
understanding of the disaster --
-
not the search and rescue.
-
The search and rescue teams had it under
control and knew what they were doing.
-
The bigger problem was that river
and mudslide might wipe them out
-
and flood the responders.
-
Not only was it challenging
to the responders and property damage,
-
it's also putting at risk the future
of salmon fishing
-
along that part of Washington state.
-
So they needed to understand
what was going on.
-
In seven hours, going from Arlington,
-
driving from the instant command post
to the site, flying the UAVs,
-
processing the data, driving back
to Arlington command post --
-
seven hours.
-
We gave them in seven hours
data that they could take
-
only two to three days
to get any other way --
-
and at higher resolution.
-
It's a game changer.
-
And don't just think about the UAVs.
-
I mean, they are sexy -- but remember,
-
80 percent of the world's
population lives by water,
-
and that means our critical
infrastructure is underwater --
-
the parts that we can't get to,
like the bridges and things like that.
-
And that's why we have
unmanned marine vehicles,
-
one type of which you've already met,
which is SARbot, a square dolphin.
-
It goes underwater and uses sonar.
-
Well, why are marine vehicles so important
-
and why are they very, very important?
-
They get overlooked.
-
Think about the Japanese tsunami --
-
400 miles of coastland totally devastated,
-
twice the amount of coastland devastated
by Hurricane Katrina in the United States.
-
You're talking about your bridges,
your pipelines, your ports -- wiped out.
-
And if you don't have a port,
you don't have a way
-
to get in enough relief supplies
to support a population.
-
That was a huge problem
at the Haiti earthquake.
-
So we need marine vehicles.
-
Now, let's look at a viewpoint
from the SARbot
-
of what they were seeing.
-
We were working on a fishing port.
-
We were able to reopen that fishing port
using her sonar in four hours.
-
That fishing port was told
it was going to be six months
-
before they could get
a manual team of divers in,
-
and it was going to take
the divers two weeks.
-
They were going to miss
the fall fishing season,
-
which was the major economy for that part,
which is kind of like their Cape Cod.
-
UMVs, very important.
-
But you know, all the robots
I've shown you have been small,
-
and that's because robots
don't do things that people do.
-
They go places people can't go.
-
And a great example of that is Bujold.
-
Unmanned ground vehicles
are particularly small,
-
so Bujold --
say hello to Bujold
-
(Laughter)
-
Bujold was used extensively
at the World Trade Center
-
to go through Towers 1, 2 and 4.
-
You're climbing into the rubble,
rappelling down, going deep in spaces.
-
And just to see the World Trade Center
from Bujold's viewpoint, look at this.
-
You're talking about a disaster
where you can't fit a person or a dog --
-
and it's on fire.
-
The only hope of getting
to a survivor way in the basement,
-
you have to go through things
that are on fire.
-
It was so hot, on one of the robots
the tracks began to melt and come off.
-
Robots don't replace people or dogs,
-
or hummingbirds or hawks or dolphins.
-
They do things new.
-
They assist the responders,
the experts, in new and innovative ways.
-
The biggest problem is not
making the robots smaller, though.
-
It's not making them more heat-resistant.
-
It's not making more sensors.
-
The biggest problem is the data,
the informatics,
-
because these people need to get
the right data at the right time.
-
So wouldn't it be great if we could have
experts immediately access the robots
-
without having to waste any time
of driving to the site,
-
so whoever's there, use their robots
over the Internet.
-
Well, let's think about that.
-
Let's think about a chemical
train derailment in a rural county.
-
What are the odds that the experts,
your chemical engineer,
-
your railroad transportation engineers,
-
have been trained on whatever UAV
that particular county happens to have?
-
Probably, like, none.
-
So we're using these kinds of interfaces
-
to allow people to use the robots
without knowing what robot they're using,
-
or even if they're using a robot or not.
-
What the robots give you,
what they give the experts, is data.
-
The problem becomes:
who gets what data when?
-
One thing to do is to ship
all the information to everybody
-
and let them sort it out.
-
Well, the problem with that is
it overwhelms the networks,
-
and worse yet, it overwhelms
the cognitive abilities
-
of each of the people trying to get
that one nugget of information
-
they need to make the decision
that's going to make the difference.
-
So we need to think
about those kinds of challenges.
-
So it's the data.
-
Going back to the World Trade Center,
-
we tried to solve that problem
by just recording the data from Bujold
-
only when she was deep in the rubble,
-
because that's what the USAR team
said they wanted.
-
What we didn't know at the time
-
was that the civil engineers
would have loved,
-
needed the data as we recorded
the box beams, the serial numbers,
-
the locations as we went into the rubble.
-
We lost valuable data, so the challenge
is getting all the data
-
and getting it to the right people.
-
Now, here's another reason.
-
We've learned that some buildings --
-
things like schools,
hospitals, city halls --
-
get inspected four times
by different agencies
-
throughout the response phases.
-
Now, we're looking, if we can get
the data from the robots to share,
-
not only can we do things like
compress that sequence of phases
-
to shorten the response time,
-
but now we can begin to do
the response in parallel.
-
Everybody can see the data.
We can shorten it that way.
-
So really, disaster robotics
is a misnomer.
-
It's not about the robots.
-
It's about the data.
-
(Applause)
-
So my challenge to you:
-
the next time you hear about a disaster,
-
look for the robots.
-
They may be underground,
they may be underwater,
-
they may be in the sky,
-
but they should be there.
-
Look for the robots,
-
because robots are coming to the rescue.
-
(Applause)