These robots come to the rescue after a disaster

Over a million people are killed

each year in disasters.

Two and a half million people
will be permanently disabled or displaced,

and 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 1,000 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 for 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 together
imagery together

and getting 3D reconstruction.

We used both of these at the Oso mudslides
up in Washington state

because the big problem was

geospatially and hydrologically
understanding the disaster,

not the search and rescue.

The search and rescue teams
had it under control:

they knew what they were doing.

The bigger problem was that river
and mudslide might wipe them out

and flood the responders,

and not only was it challening
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, from 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.

The 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 busheld.

Unmanned ground vehicles
are particularly small,

so bushel

-- say hello to bushel (Laughter) --

bushel was used extensively
at the World Trade Center

to go through Towers 1, 2, and 3.

You're climbing into the rubble,
rappelling down,

going deep in spaces,

and just to see the World Trade Center
from busheld's view,

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, 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.

At the World Trade Center,
going back to the World Trade Center,

we tried to solve that problem
by just recording the data from busheld

only when she was deep in the rubble,

because that's what the user 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)