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Discovery Channel
Discovery Channel

How Scientists Built a Shark-Following Robot for Shark Week

Discovery Channel
Discovery Channel

For all we know about sharks, there's still a lot we don't know about these animals that both fascinate and terrify us. Traditional tracking methods like satellite and acoustic tags have shed some light on shark behavior, but even they have their limitations.

That's where Shark Cam, an autonomous underwater vehicle, comes in. "A few years [ago], I was working with a scientist who loved the idea of trying to find out what some of these fish that we track do when we can’t follow them because they’re out of reach or they go deep or we disturb them when we get in the water," says marine biologist Greg Skomal. "We thought it’d be really interesting to develop some kind of robot that could track marine animals, specifically sharks. One of the principals at Big Wave Productions [which produces shows for Shark Week] was super excited about the concept and propelled it upwards to Discovery, and they loved it. So with their support, we were able to actually make this come to fruition."

The autonomous underwater vehicle (AUV) was developed by Skomal and scientists at the Oceanographic Systems Laboratory at Woods Hole Oceanographic Institution. It was deployed from a boat off of Chattam, Massachussets, last year, where it followed great white sharks as they swam along the coast. Shark Cam makes its debut in the Shark Week special "Return of Jaws" tonight at 9 p.m. EST on the Discovery Channel; we talked to Skomal about developing the robot and what it revealed that traditional tracking methods did not.

How long did it take to build and deploy Shark Cam?

We started the project in 2011, and were able to do some field trials in late 2011, and we had a pretty functional vehicle by the summer of 2012. So about a year of solid development. Most of that was software modifications by the engineers who run these robotic underwater vehicles.

When you’re building something like this, are you working from an existing platform or are you starting from scratch?

The Oceanographic Systems Laboratory at Woods Hole Oceanographic Institution has an existing group of vehicles that are autonomous—they’re completely untethered to the boat, and they can be programmed to do a variety of missions. So really, all we had to do was modify the software of one their existing vehicles in order to get it to follow a live shark.

It sounds simple, but it wasn’t. It was a partnership—[between the engineers and] me, having tracked fish for years, trying to give them a sense of what we anticipate the behavior of the shark to be, so that the vehicle can adjust to it. It’s one thing to have a vehicle go in a straight line, or even mow a lawn—back and forth, back and forth—but to have it adjust to the behavior of a live animal is a most complex process.

What kind of behaviors would they be adjusting for?

Changes in three-dimensional movement. Up, down, sideways, back, forth—you name it. Very few live animals swim in a straight line at one depth. So it had to basically adapt to random movements in three-dimensional space.

What technology did you outfit the robot with?

There were four cameras on Shark Cam—it was specially designed to carry three of those, and one mounted on top. It's battery-powered, which limits its life, but that’s fine, we can expand on that. It is modular in the sense that we can add components to it that do various kinds of things that we did not do [on this mission], like collect oceanographic data. It communicates with a transponder that we put on the shark to follow it and navigate and recreate the track of the animal.

We actually added a rear-facing camera, but because of the fine balance on the vehicle itself—it’s a torpedo and it has to be extremely hydrodynamic—throwing the extra camera on slowed it down. So that’s something that we have to develop in the next phase of this operation.

Robot with a view. Photo courtesy of the Discovery Channel.

When you decided you were going to take the Shark Cam out and put in the water and send it after a shark, you guys had to go out and tag the shark first. How did the robot work in conjunction with the acoustic tags?

We’ve been tracking white sharks with a variety of technology off the coast of Cape Cod for the last four summers. So [tagging the sharks was] almost the easiest part, since we’d already done the [research and development] to get that done. Once we got the transponder on the shark, the AUV was set to go.

Most acoustic transmitters emit a ping, and the ping is picked up by people in the tracking vehicle, so we can track the fish. But this acoustic tag is a transponder, so it has two-way communication between the vehicle itself and, in essence, the shark. So we can basically have a conversation that provides for highly precise navigation and mapping of three-dimensional movement. And that really is a step forward, because it’s not just passive acoustics where you’ve got a vehicle trying to just listen for something. [The AUV] was actually listening and communicating with [the tag].

We had to program the vehicle so that it could make decisions—very simple cause and effect decisions based on where the shark was, to follow it. We ended up getting a vehicle that can give us very precise tracks of the animal.

Were there any glitches you had to work out?

There was a whole series of glitches. The transponder itself is larger than we want it, but the funding simply wasn’t there to miniaturize it. So we had to use what we had. It turns out the orientation of the existing transponder design had to be vertical in the water column, which is absolutely counter to normal hydrodynamics. We had to figure out a way to get it to tow vertically on the shark, and that took a few days working with our tagging crew and the engineers. And that would allow for a stronger signal so that the AUV could actually keep up with the shark in shallow water.

We’re also in the natural environment. Where these white sharks hang out is a very dynamic area in terms of tide and current. So in many ways, we’re up against trying to get a vehicle that can only go, you know, six miles an hour to keep up with a shark that was swimming steadily at five miles an hour. And then it was the fine-tuning of the vehicle so that it could stay with the shark and not lose it.

How did the sharks react to it?

Jokingly, I told the engineers that once this big white shark sees this vehicle, painted bright yum-yum yellow, it was going to turn around and just eat it. Most would think that this voracious animal that is considered to be one of the most dangerous one on earth would not like to be followed so closely. So these guys got nervous every time the AUV got in close proximity to a shark.

But the shark completely ignored it. [At one point,] the shark actually turned around and did a big loop and started following the AUV, which I thought was fantastic. The AUV couldn’t do anything about it—it was hearing the shark behind it, and a major limitation of the technology is that it can’t do hairpin turns and quick circles. So that made for some good humor.

What did you learn by deploying this robot that you couldn’t learn just from using acoustic tags or satellite tags?

Every tag in technology has its ups and downs, and there’s no silver bullet when it comes to tags that gives you high resolution, broad scale, and fine-scale data on movement. Satellite tags are really good for looking at broad-scale movement—where the shark goes in broad migratory patterns. It doesn’t tell you a lot about fine-scale behavior.

Acoustic tags will tell you a little bit about fine-scale behavior, but only in the sense that you know where the shark is at any given time. One of the problems with the technology of acoustic tags—prior to us doing this—was instead of sending a robot after a shark, you follow the shark with your boat. And that’s usually limited by weather considerations, fuel, compatibility of crew members, provisions, all those things that can come up and go wrong. And the boat’s track doesn’t necessarily reflect the shark’s track, because the shark is going to be somewhere within a quarter or a half a mile from the boat. And it’s really hard to get a good, precise estimate of the actual movements of the shark in three-dimensional space using traditional tracking methods.

With the ability to send robots after the shark, you’re going to increase the precision of your tracking so you’ll know exactly what the shark did in three-dimensional space—the depth of water, the depth of the shark—and you’re collecting data at the same time over that same path. The vehicles can carry instrumentation on them—the simplest being water temperature, to complex instrumentation that measures current and tide—so you can determine whether the shark is swimming upstream or downstream. You can look at dissolved oxygen, so you can get a sense of what the minimal oxygen requirements of the shark are. You can also add other kinds of instrumentation that’ll answer questions about the habitat in which the shark lives.

So it’s a huge step forward—and when you throw cameras on the whole thing, you even have the potential for real behavioral observation: To see what the shark is doing. Let’s say it stops swimming and just stays in one area. If we approach it and put divers in the water, that’s going to spook the shark—and very few divers want to jump on top of a white shark to begin with. Or you speed up on it on a boat and you try to see what the shark is doing, but what if it’s 30 feet underwater? You can’t see what it’s doing. You send Shark Cam out, and you can record what’s going on in that area.

So the robot is a proxy for what we can’t do, and I think it’s a huge step forward in terms of advancing science and adding a new tool for marine scientists.

Have you used Shark Cam since?

We have not deployed the Shark Cam since last summer. The next step is going back to the drawing board—raising funding to tweak it and take it to the next level.

What's the next level?

The next level for us is to improve upon and learn from what we’ve already done. It’s a real solid analysis of the data, it’s fine-tuning the software to take into account sudden modifications in the shark’s behavior. It’s probably to integrate the camera systems a little better with the AUV so that we may be able to control them—turn them on, turn them off. It’s energy budgeting. And it’s really miniaturizing the transponder so that we can put it on much smaller sharks and maybe broaden its applicability.

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Animals
Why Tiny 'Hedgehog Highways' Are Popping Up Around London
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iStock

Hedgehogs as pets have gained popularity in recent years, but in many parts of the world, they're still wild animals. That includes London, where close to a million of the creatures roam streets, parks, and gardens, seeking out wood and vegetation to take refuge in. Now, Atlas Obscura reports that animal activists are transforming the city into a more hospitable environment for hedgehogs.

Barnes Hedgehogs, a group founded by Michel Birkenwald in the London neighborhood of Barnes four years ago, is responsible for drilling tiny "hedgehog highways" through walls around London. The passages are just wide enough for the animals to climb through, making it easier for them to travel from one green space to the next.

London's wild hedgehog population has seen a sharp decline in recent decades. Though it's hard to pin down accurate numbers for the elusive animals, surveys have shown that the British population has dwindled by tens of millions since the 1950s. This is due to factors like human development and habitat destruction by farmers who aren't fond of the unattractive shrubs, hedges, and dead wood that hedgehogs use as their homes.

When such environments are left to grow, they can still be hard for hedgehogs to access. Carving hedgehog highways through the stone partitions and wooden fences bordering parks and gardens is one way Barnes Hedgehogs is making life in the big city a little easier for its most prickly residents.

[h/t Atlas Obscura]

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Penn Vet Working Dog Center
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Stones, Bones, and Wrecks
New Program Trains Dogs to Sniff Out Art Smugglers
Penn Vet Working Dog Center
Penn Vet Working Dog Center

Soon, the dogs you see sniffing out contraband at airports may not be searching for drugs or smuggled Spanish ham. They might be looking for stolen treasures.

K-9 Artifact Finders, a new collaboration between New Hampshire-based cultural heritage law firm Red Arch and the University of Pennsylvania, is training dogs to root out stolen antiquities looted from archaeological sites and museums. The dogs would be stopping them at borders before the items can be sold elsewhere on the black market.

The illegal antiquities trade nets more than $3 billion per year around the world, and trafficking hits countries dealing with ongoing conflict, like Syria and Iraq today, particularly hard. By one estimate, around half a million artifacts were stolen from museums and archaeological sites throughout Iraq between 2003 and 2005 alone. (Famously, the craft-supply chain Hobby Lobby was fined $3 million in 2017 for buying thousands of ancient artifacts looted from Iraq.) In Syria, the Islamic State has been known to loot and sell ancient artifacts including statues, jewelry, and art to fund its operations.

But the problem spans across the world. Between 2007 and 2016, U.S. Customs and Border Control discovered more than 7800 cultural artifacts in the U.S. looted from 30 different countries.

A yellow Lab sniffs a metal cage designed to train dogs on scent detection.
Penn Vet Working Dog Center

K-9 Artifact Finders is the brainchild of Rick St. Hilaire, the executive director of Red Arch. His non-profit firm researches cultural heritage property law and preservation policy, including studying archaeological site looting and antiquities trafficking. Back in 2015, St. Hilaire was reading an article about a working dog trained to sniff out electronics that was able to find USB drives, SD cards, and other data storage devices. He wondered, if dogs could be trained to identify the scents of inorganic materials that make up electronics, could they be trained to sniff out ancient pottery?

To find out, St. Hilaire tells Mental Floss, he contacted the Penn Vet Working Dog Center, a research and training center for detection dogs. In December 2017, Red Arch, the Working Dog Center, and the Penn Museum (which is providing the artifacts to train the dogs) launched K-9 Artifact Finders, and in late January 2018, the five dogs selected for the project began their training, starting with learning the distinct smell of ancient pottery.

“Our theory is, it is a porous material that’s going to have a lot more odor than, say, a metal,” says Cindy Otto, the executive director of the Penn Vet Working Dog Center and the project’s principal investigator.

As you might imagine, museum curators may not be keen on exposing fragile ancient materials to four Labrador retrievers and a German shepherd, and the Working Dog Center didn’t want to take any risks with the Penn Museum’s priceless artifacts. So instead of letting the dogs have free rein to sniff the materials themselves, the project is using cotton balls. The researchers seal the artifacts (broken shards of Syrian pottery) in airtight bags with a cotton ball for 72 hours, then ask the dogs to find the cotton balls in the lab. They’re being trained to disregard the smell of the cotton ball itself, the smell of the bag it was stored in, and ideally, the smell of modern-day pottery, eventually being able to zero in on the smell that distinguishes ancient pottery specifically.

A dog looks out over the metal "pinhweel" training mechanism.
Penn Vet Working Dog Center

“The dogs are responding well,” Otto tells Mental Floss, explaining that the training program is at the stage of "exposing them to the odor and having them recognize it.”

The dogs involved in the project were chosen for their calm-but-curious demeanors and sensitive noses (one also works as a drug-detection dog when she’s not training on pottery). They had to be motivated enough to want to hunt down the cotton balls, but not aggressive or easily distracted.

Right now, the dogs train three days a week, and will continue to work on their pottery-detection skills for the first stage of the project, which the researchers expect will last for the next nine months. Depending on how the first phase of the training goes, the researchers hope to be able to then take the dogs out into the field to see if they can find the odor of ancient pottery in real-life situations, like in suitcases, rather than in a laboratory setting. Eventually, they also hope to train the dogs on other types of objects, and perhaps even pinpoint the chemical signatures that make artifacts smell distinct.

Pottery-sniffing dogs won’t be showing up at airport customs or on shipping docks soon, but one day, they could be as common as drug-sniffing canines. If dogs can detect low blood sugar or find a tiny USB drive hidden in a house, surely they can figure out if you’re smuggling a sculpture made thousands of years ago in your suitcase.

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