>> Wayne R. Lusardi: So in Michigan there are about 1,500 known shipwrecks in Michigan waters around the
Great Lakes. Most of them are from the 19th century, so they're schooners and barks and
brigs and things like that, and in the turn of the century end of the 1800s early 1900s
there are many more steamers and paddle wheelers, propellers, bulk freighters, package freighters.
>> Narrator: Worldwide, 3 million shipwrecks are estimated to lie in the bottom of oceans
and lakes. Less than one percent of these wrecks have actually been found.
>> Guy Meadows: I've spent 45 years of my life looking for shipwrecks,
but 98% of that time is looking at wonderful images of absolutely nothing.
>> Narrator: Now, a team led by University of Michigan robotics professor, Katie Skinner,
is developing technology that will explore the sea floor much as a human would. It uses
artificial intelligence to scour sonar data and quickly identify areas that warrant a closer look.
Initial tests are taking place on Lake Huron in Northern Michigan.
>> Katie Skinner: So right now we're at the Alpena Marina. This is our kind of starting
point for every mission. We can go out from here to the Thunder Bay National Marine Sanctuary.
Thunder Bay has a hundred known shipwreck sites and 100, up to 100 unknown sites or undiscovered
sites. We'll start with the known shipwrecks here but hopefully we'll discover something new too.
>> “So, we're going to adjust the survey pattern
to hopefully fly over both wrecks in a single underwater mission.“
>> Meadows: I mean the hopes and dreams is to be able to teach autonomous vehicles how to
really search the seabed and to recognize the important things on the bottom for
finding wrecks from all the other natural occurring things on the bottom of the water.
>> Skinner: So, we just deployed the IVER for its first mission of the day.
So we deployed off the side of the boat, we watch it go to its first waypoint on
the surface and then it will dive down for the first leg. We programmed a lawnmower pattern,
which means it will do eight different legs in kind of a lawnmower fashion for this survey.
>> Meadows: What we're trying to look at is, we know where the shipwreck is,
this is a well known wreck, but we're looking for clues that would teach underwater vehicles
like ours to be able to find wrecks more efficiently. So we're looking for patterns
in the bottom debris that may have fallen off the ship during the time it was sinking.
>> Narrator: The system can look for clues in the vast amount of existing sonar data
that's publicly available. It can also help new missions find areas of interest more quickly.
>> “So this is a sonar image of Lucinda Van Valkenburg Schooner here that wrecked in Thunder
Bay as a result of collision, and we're able to see kind of a sort of a planned view going
right over the top of the wreck and you can kind of see the debris field at the stern. “
>> Narrator: While using underwater vehicles and sonar is not new, teaching computers to
autonomously identify the best areas to explore is on the cutting edge of this technology.
>> Skinner: Yes, we can think about the shipwreck detection problem similar to anomaly detection,
so we want to give the system a lot of experience of seeing large amounts of data
that doesn't necessarily have shipwrecks it's just about the general terrain and
this allows it to learn what those features are in the general terrain so when it comes
across new features like shipwreck sites or other archaeological sites of interest it
can recognize that that is something that it hasn't really seen before.
>> “AV just popped up over here.”
>> “Yeah I think we're gonna pull it in.”
>> “Yep we're gonna pull in IVER.”
>>“Right now I'm copying some of the sonar data off the vehicle that we just recovered.“
>> Meadows: The problem we're trying to solve and many people are facing this problem, Malaysian
Flight 370 is a perfect example. The clues are that it was lost somewhere in the Indian Ocean,
and it's an enormous amount of territory to try and cover with sonar in order to see something
like a wreck whether it's an airplane or whether it's a ship and the same is true here in the Great
Lakes. We need to have ways to be able to refine the search to areas that are most probable to
contain clues about the wreck so that is the main problem that we're trying to solve here.
>> Narrator: A successful automated system could help us understand the ocean and lake floor
and uncover secrets still hidden beneath the sea.