In this episode, Audrow Nash speaks to Ben Raana, who is a software engineer at the Monterey Bay Aquarium Research Institute (MBARI). MBARI uses robots to monitor and explore the oceans to better understand climate change and other topics. Ben speaks about how robotics is enabling ocean research, the challenges of putting a robot in the ocean, how their robot platform works, and how they are working towards long-term deployments.

Start

Introducing Ben and MBARI

Understanding human impact on the ocean

Using robots for scalability

Collecting ocean data

Describing their ocean robots

Power management

Varying the buoyancy

Their robot’s cost

Communicating with the robot

Failure management + safety precautions

Growing the fleet

Simulation with Gazebo + open source

Future of missions

Advice for those looking to contribute to ocean research

This is a conversation with Ben Raanan who is a software engineer at the Monterey Bay Aquarium Research Institute, or MBARI, for short. MBARI uses robots to monitor and explore the oceans to better understand climate change, and other topics. In general, getting ocean data is extremely expensive. Depending on how far the area of interest is from the shore, it may require a large boat with a full crew. MBARI is working to make this process easier and much cheaper by having robots stay at sea for weeks at a time getting data on different ocean events. This generates a lot more data and will hopefully greatly improve our understanding of our oceans. I found it exciting to talk with Ben about how MBARI is looking into having robots stay at sea almost indefinitely, charging their batteries and uploading their data all while at sea. This could enable fleets of robots to continuously be at sea giving us a much richer picture of the health of our oceans. I'm Audrow Nash. This is the Sense Think Act Podcast. Thank you to our founding sponsor Open Robotics. And now here's my conversation with Ben Ron on. Hi, Ben, would you introduce yourself?

Sure. Hi. My name is Ben Ron on a oceanographer and robotics software engineers here at the Monterey Bay Aquarium Research Institute. Or we're in MBARI, for sure. We're in Barcelona, California. I've been here with the Institute for probably coming on years now. Working as an engineer, a bedroom about my background, actually, motion career about 20 years ago, I was a special warfare operator and a combat diver in the Israeli Navy. And spent a good chunk of time with the teams there. And later on, got my undergrad in r&d tax and biotechnology back home in Israel. And then came here to get my Master's in physical oceanography. At that point, I got involved here with the Institute through an internship, and then I just refused to leave. Yeah, so now mostly what I do is I work development and operations with autonomous underwater vehicles. And so I have a few projects running, but I think you're interested in looking for talking about

awesome. So what kinds of projects do you guys do at MBARI?

Yeah, so I guess maybe we before we dive into the projects, can tell you a little more about embargo in general, I think, sure, you may be familiar, but others may not. So like I said, we're in Moss Landing Fornia in the Central California, say probably about an hour south, from San Jose, on the coastline, in the Monterey Bay. And in MBARI is actually a pretty unique Ocean Research Institute, in the sense where we're a private nonprofit. So the institute is not an academic Institute, it's kind of been founded as an alternative to what an academic Institute can be for ocean research, in bars funded almost exclusively, through the David and Lucile Packard Foundation. And David Packard, which is the P and HP and Hewlett Packard, he founded this, yeah, he founded this institute in 1987. So we just celebrated our 35th birthday. And the mission back then was to, like I said, offer an alternative to traditional academic research institutes, and take on challenges that require development of technology in order to, you know, answer some of the scientific questions that marine scientists have. And so that's kind of been the goal of Institute and also remove a lot of the, I guess, barriers, especially when it comes to funding. And so scientists and engineers here get to focus more on the doing and less than they're proposing. And so we have an internal proposal cycle, in which we, you know, for our budget, and then we get funded through Packard Foundation, which is phenomenal, it's absolutely great. And so, the type of the way the institute is structured is we're actually kind of like a three legged stool. And our trifecta, never skip on an opportunity to say that word. And so, so, the Institute has about 220 employees. We are divided into science, engineering, and Marine Operations. And we work very closely together. So Though the barrier or the the boundaries between the groups is very blurred, you know, you got a lot of scientists that are very much engineers and engineers that are scientists and they work together to find the questions that need to be answered. And then develop the technology that allows us to go out and get that. And then the Department of Marine Operations has the specialty in the knowledge and how to deploy the assets and manage, you know, so you know, make sure everything comes back safely, to the best of their ability. And so that together is what I think really makes the institute special in its ability to come up with very challenging questions, develop the technology to try and gather the information that's required in order to answer those questions. And then actually go in the field, gather the data, and and you know, start working on the answers. And so that's kind of like a cycle that we exercise here pretty regularly. And it's it's all good fun. So I guess that's the institute is the that's the answer to in in in a nutshell.

And what kind of problems are you guys typically like also the in Hewlett Packard, so Packard set this foundation, or set this up? So he received or he sends you guys a good number, a good amount of money? To do the research? What kinds of problems? Are you guys most interested in? Solving? Or, like, what what kind of problems are you going after? I guess, yeah.

So if you walk around the hall here, you'll find scientists pretty much any ocean research discipline that you can imagine. So we have geologists, geophysicist, chemical oceanographers, biological oceanographers, any kind of type of marine research really, that you can imagine, is happening here. And so at the core, we're trying to describe the ocean environment and go after questions that also have to do with anthropogenic impact, that's driving change in the ocean environment,

is human generated? So, yeah, so that really relates to some of the challenges that are faced with climate change, and how emissions for example, impact our environment. And so, the ocean is actually a really important piece and buffering the heat on the planet. And so, in order to understand better the processes that govern heat transfer, how carbon dioxide that gets emitted into the atmosphere is gets absorbed and back in the ocean and and buried in the in the ground, that's, you know, the carbon cycle. So, the Institute is trying to target research in order to acquire data and figure out how what governs these processes, what are the rates, and then through this research inform larger models that have to do with you know, climate change and more of a global scale in the global scale sense. So, those kinds of questions they really drive research in all the layers of the ocean. So, from the atmospheric to you know, the upper water column, where the gases kind of mix and then how the biology interacts with the different chemical properties of the water, different physical properties of the water, they take in some of this carbon and use it to build their bodies right through photosynthesis, and that later on feeds the larger organisms and cascades through the foodweb and eventually, those kind of fix organic compounds are either pooped out or die and sink to the bottom of the ocean right and get buried there. And so that okay, is the carbon cycle in a nutshell and we focus on research that tries to describe each of those sections in detail, and then

yeah, gotcha. So, you have just to see if I understand the carbon cycle, you have carbon in the environment, then you have small like algae or something, some small things. that will consume the carbon and sunlight in this kind of thing and the photosynthesis happens, then they go through this whole process where they're eaten by fish or something. And somehow, they like eaten by one fish that small, a bigger fish eats that whatever, eventually something dies in there. And then it sinks to the bottom of the ocean. And what happens when it's at the bottom of the ocean? It kind of just stays there for a while. And you get kind of like, on the bottom of the ocean, or

Yeah, so it gets it gets vented is sediment, and ocean sea floor, really is, I guess the storage of that moment, until, you know, either gets, then you're starting to look at geological processes on you know, what happens there? How? Yeah, so how does the ocean seafloor evolve over time? And when does that carbon make it back into the atmosphere? And so I guess the point is, yeah, so we describe a lot. And I guess the point to really kind of take away from this is that these are processes that happen over many, many, many timescales and over very different, yeah, are very different spatial scales as well. And so at MBARI, we kind of talk about it in the sense of, you know, going from molecules and atoms to ecosystems and back. And so the type of science that we do hear goes from, but understanding the microbial processes that you know, what type of nutrients are required in the ocean in order to make these biological plankton or bacteria flourish and take in these gases, then, all the way up to how does it later cascade into the food web? And what are the timescales that are associated with those things, and so that, on its own poses many challenges, because in order to collect relevant information, to describe these processes, you really have to be at sea a lot, and have to be there not only for the duration, but also in the right place, and cover and span, you know, the area that's required in order to to really capture those fundamentals. So

if I understand correctly, it sounds like you guys are basically trying to model so the carbon cycle and what's occurring to accurately model that and have a better idea for climate change, you need to be involved at something through the whole spectrum, which is a massive process that happens everywhere in the ocean, at all different times, with all different creatures, there's lots of things involved. And so because of this, this makes it so you guys have a very large research mission. In a sense, like, there's a lot of things that you need to understand, or there's a lot of monitoring that needs to happen. So that you can begin to refine your model. So you can have a good idea of this process, and maybe its impact, or maybe its changes over time. And these kinds of things.

Exactly. And the idea is that eventually, those type of this type of information, can cascade into decision makers for conservation management, and other type of, you know, decisions that impact our environment, but also can affect some of the likelihood, for example, fishermen, and so on.

So that sounds incredibly lofty as in a huge, huge challenge to basically take on climate change. Is that motivating everything at MBARI? Or are there other problems that you guys are interested in to? Like, clearly enormous? And that's is that everything under that umbrella? Or are there other umbrellas?

Well, there are other themes as well. I mean, you have researchers here, for example, that are behavioral ecologists, and they're interested

in I don't even know what that means at all.

Oh, they're, they're interested in in describing, you know, how certain species behave under underwater and so. Right? So you can imagine, for example, if you're interested in studying squids, especially if you're interested in studying DP squids, then, again, getting access to to the environment where those squids are, is an enormous challenge. And one that's very suited for institute that is, you know, capable of developing the technologies and also executing the operations for getting the right information and so on. You know, that's another type of research that we do here. We also have a whole mapping division, we use vehicles to go in and do surveys of the ocean seafloor and map the ocean seafloor, and then return to see how it evolves over time. So that's a whole kind of branch of geology that we host here. So really, it's it's very hard to try to capture all the activities that go on here and the Institute, I'd say, climate change has definitely been one of the main themes and impacts of climate change on the ocean environment has been one of the main themes that have governed a lot of the proposals and the projects that have been here. But it's not the only one, you know, they're there. Other projects that, you know, maybe don't fall exactly under that umbrella. But that is definitely the the lead theme.

Gotcha. And largely ocean related. I mean, well, entirely ocean related, it sounds and then it's also, I mean, if you have better ideas of how these creatures behave, maybe you have a better idea of how they are as actors in the system, which helps you model these things. And if you have better maps of the environment, perhaps that also helps you in environmental monitoring, I could imagine, which will go back into climate change, in some sense, because it's such a large problem, that having an accurate model has so many pieces to

correct. And then I guess I'll add that embargo has been a major player, you know, since the 80s, collecting this information. And so at this point, we've gathered enormous quantities of data. And we are working pretty hard to make this data available for others to use, and also process it here and have that multi-decadal perspective, in order to quantify change in the environment. So in other words, we are establishing a baseline starting, you know, from some point, and looking and observing how the environment changes over time. And so another big mission of embargo is to, you know, safeguard this trove of data and make it accessible. And so I think that's another thing that the Institute is unique in its capacity to offer. So

that's really cool. Now, so that's awesome. What are some of the ways that you guys have been using robots and these different parts of kind of the mission of MBARI?

Right, so um, you know, we refer to oceanography here as a contact sport, like I mentioned, in order to gather the data, you have to be in the environment. And so as you know, traditionally, oceanography for decades and has been done using ships. And that's great. I think that ships and humans are always going to be part of this type of research. And inquiry, indeed, operates to large ships that go out and collect data and take expeditions at the sea. But I think there's also a realization that, you know, because of these temporal and spatial scales in which the phenomenon that we're interested in studying happen, we're just not able to

get all the clients to be everywhere all at once, for sure. So it's much easier to have robots go do it, for

sure. Not impossible, but it is cost prohibitive.

Yes. But that also human error and all sorts of other things, too.

Sure. I mean, robots make mistakes, also, especially people that operate them. So, in fact, because, you know, traditionally, this type of research has been done using chips. MBARIs also put a lot of resources into calibrating the measurements. Okay. So you've done it collected data, in a certain way, for a certain number of years, and now you're switching into a more automated collection system. And so how does that data compare? And what are the calibration factors that you need to apply to go from, you know, manually collected systems into using data that's collected by automated systems. And so that's, so making

sure that we have consistency from humans taking it too. Maybe if you can automate it and have a robot do it, you want them to be apples to apples, not apples to oranges. So you have this big break? where the data is, like, completely different and hard to draw conclusions from?

Exactly. So you don't suddenly think that there's, you know, some kind of climate crisis that happens to coincide with the time you started using certain robots. So so we've been seeing through this transition. Now, some of the environments that we researched which are very hard to get to. So, for example, kind of the average ocean depth here in the Pacific is about four, four and a half kilometers. So, so just those are

four and a half kilometers. That 45 football fields deep, roughly or,

rightly so. Yeah. And a lot of weaker but yeah, sorry. Yeah, so so so that's very deep. And when you think about, for example, the type of pressure Vironment that we live in. We live at one atmosphere of pressure, if you go to space, you're almost at zero. But if you go about 30 feet down into water, then you've already doubled the pressure. And every 30 feet, you add, you add a whole nother atmosphere. So

those many atmospheres are down there, then

It's one atmosphere per 10 meters. So if you have 4500 meters, then you'd be at

divided by 3030 feet per or 10 meters is one atmospheric, correct?

Yeah. So 450 atmospheres, I believe is the number.

Yeah, that's an easy one. Yeah, doing math doesn't always

work. But especially not not. Well, you're being recorded.

Correct. So I guess the pressure is immense. And so in order to take humans into those kinds of environments, and support life, human life, in those environments, you know, it comes with a huge overhead. And it's not risk free. And there are systems that do that. You know, we have deep sea sobs. Woods Hole Oceanographic, I believe, operates. Alvin, which is a human submarine that's able to go to those kinds of depths and and collecting through there. But it's really scalable. And you say,

on average, just average depth is that much, right? What's the what's the deepest? Like, I guess we probably don't have a very clear idea. But what so we do. Okay, yeah. So how far down does it go?

It's over 11 kilometers. taller than the mount, the tallest mountain, right? So and that's 1100. atmospheres. Correct. And I believe that's the Mariana Trench, off the coast of Japan, which is, so yeah, it's pretty deep, but humans have reached there. And vehicles have gone down there as well. And so it's not out of their reach. So it's not very scalable. Right, I guess it's the point. And, like I mentioned, again, a lot of the phenomenon that we're also interested in, in studying are very patchy and episodic in nature, meaning, you can imagine the wind blows a certain direction, the currents do a certain thing, the nutrients emerge, and then suddenly, boom, that creates an opportunity for something to occur. And you're either there, or you're not. And sometimes you can be, I'm sorry,

give me an example. Like what might an event that you're trying to see occur be like an algae bloom of some sort, or

Yeah, that'd be a classic example. And so typically, the way this occurs is winds blow, they push coastal waters away from shore, and pull in deeper waters that are much richer in nutrients. And that allows for this community to community of microorganisms, plankton, and phytoplankton, to really flourish. And that mostly happens on the, you know, upper part of the ocean where there's access to sunlight. And so when those conditions come together, and those blue dunes are, you know, you're either there to catch it, or you're not. And you either have a platform that's able to go out and collect this information, or you don't. And so, I guess, once that window of opportunity closes, and typically that's on the order of, yeah, weeks, spanning 10s of kilometers, at least in the coastal environment. Yeah, that then your window of opportunity is is gone and you've lost your chance to collect the relevant data. And so having having autonomous platforms that are able to persistently be in the ocean and collect information is a huge advantage. And so we kind of segwayed away from the deep ocean back, you know, to the upper water column and we operate automated In automated systems in both, but you either need a very a system that's capable of operating into depths and in those deaths, or you need a system that can operate up in the water and the upper water column that's, you know, capable of having that persistence and endurance to cover, you know, those, those those areas. And so in both cases, that those type of problems lend themselves very well, for automation, and for use of autonomous platforms. And so MBARI has developed. You know, at the beginning, we were very focused on getting to those steps. And so MBARI was one of the pioneers in developing remotely operated vehicles, there was a big kind of cube like, vehicles, remotely operated vehicles are over. Okay. Which, yeah, and so, those are tethered vehicles, and they're piloted remotely from a ship. So those still require a ship to be in the area. And then bears

able, correct, yeah, going from the robot to the ship. Yeah. Yeah, correct.

And so in borrowing has been invested heavily in developing those kinds of debit technologies, and also coming up with ways to manipulate, you know, the environment there with robotic arms, and so on, so forth. And then more recently, we focused on using autonomous vehicles to extend the duration. So cutting the tether, focusing on platforms that can sustain themselves in the environment, with a remote operator that only supervises periodically. And that really gives you a ability to design without counting on having a ship in the area. And B, it also opens the window for scalability, right? So

because you don't need that big stack, to maintain and be running, like you don't need a whole ship, going to the one location because you just have a bunch of these making their way around the ocean, monitoring things

correct. And you can also have an operator that rather than being fully engaged in operating a machine is now checking in periodically just to make sure things are happening as they should, and maybe providing instructions for correction. And so

the grocery store checkout model is everywhere, these days, for this kind of thing, where you have like the one person watching the 10 machines that were it's just it's so interesting to see it here to where you have one person kind of supervising, but not paying attention all the time to all of the robots in your groups, but just watching a few that periodically come in and out of contact, and they manage maybe giving high level directions or something like this. It's so interesting, this is becoming everywhere, it seems.

Yeah. And I guess the so there are some aspects of doing marine robotics that I guess they're very different from terrestrial robots, or aerial robots in a sense. So I think, you know, the underwater environment is a communication denied. Environment, meaning, you know, once you go on your, the radio frequencies that we use for localization and radio in between our vehicles diminishes, at that point, we're only the only chance to our only option to communicate with the vehicles mystically using sound underwater. And that presents a whole nother set of challenges. And that technology has come a long way. But it's still very limited, especially compared to way lower bandwidth

I would imagine. Correct. So you're, you're talking about far less information can be sent,

right bits per second, and then three limited in range with typical range, you know, I'd say a few kilometers, is kind of typical. Yeah, so So the vehicles really need to be self sustained. And they need to know what to do and operate on their own. And so that that's a challenge. But at the same time, you know, as humans, we're not really able to be in that environment, it's hostile for our bodies. So any kind of system they can put out there and can execute a task that's useful is going to be an improvement of what you know, on top of what a person can do. And I feel here in terrestrial robotics, we're always up to your challenge, because, you know, you got to do as well as something that as well as a human where you're already in an environment where humans can function fairly well. So so we have it, you know, many challenges of one one had but then, you know, in some, in some ways, it's kind of easier to make fast progress and push the needle further than what you would be able to Have you used in environments where humans are capable?

Yeah, because it's so cheap. So I'm a little confused. But it. So you're saying, because these environments are so challenging to get people out there, and there's budget restrictions and things because like, you can't have a ship go to each location you need, or you're interested, but you can have a robot that kind of manages itself much more cheaply. And so because it's so hostile, and because of the scalability problem, there's a lot of room for advancement with these robots that are going at the kind of the shallow depths and monitoring things autonomously.

Correct, or? No? Yeah, I mean, there's, there's just pretty much any kind of, if you can get a system to execute any kind of task out there at sea, you're already pushing the needle forward, you're improving over what a human can do. And so and so I guess that's one advantage of doing marine robotics, but it might be the only one, because it really is very hard. It really is. Environment.

Oh, yeah, totally. I imagined it's like, almost, if not as difficult as like putting a robot in that, like, if you put a robot in space, it's like tremendously difficult to get it up there. But once it's there, and it's in a harsh environment, it's that's a big challenge, for sure, like putting a rover on the moon, or putting a rover on Mars or putting something in space. Like that's tremendously challenging, given the harshness of that environment, and that the remoteness of it. But this is kind of similar in that the environments like water is really powerful. It's very cold, it's very rough. There's like, I don't know, bunch of creatures all around, I don't know, I'm imagining like,

we did have vehicles in the past. So vehicles have returned with shark bites in them and teeth embedded in wirings. But that's actually a really good comparison. But I guess I would argue that, you know, because of the pressure and space versus pressure at sea, we've already talked about that. So we call that yeah, you need to be able to sustain those pressures, which, you know, is a challenge, but also, even a vehicle on Mars. Sure, you have a 20 minutes to 20 minutes back delay in your communication, but you're still able to communicate with the vehicle at all times. Versus Right, exactly. Versus underwater platform, where once the vehicle is under you typically lose contact. So yeah,

that's very interesting for that. It's definitely a very hard problem space. One thing just to give it because this is one thing that I don't quite understand yet. What kinds of things because these robots are out there, and they're monitoring something. But what kinds of data are they collecting? While they're out there? Like, specifically? And I'm sure there's a lot of things you could look at, but like the nature of the type of data, you're collecting, something I don't yet understand?

Sure, yeah. So we have platforms, different platforms are geared toward collecting different types of information. And so if you're looking at an ROV, that's a remotely operated vehicle that has the option to manipulate. And so you little hands, right, exactly. Okay, so you can do specimen collection, for example, at the deep sea. We also use those type of platforms to do surveys of the seafloor using video multibeam sonars. And also for mapping and also, now, LIDAR. And

that works under I mean, I guess it makes sense that it works underwater. I imagine there's a new set of problems and challenges with that.

Yes, it's very challenging. I'm actually not working on those projects. But we have a whole team here that's developing that capability. And it's pretty cool, actually. Oh, yeah. So so they've developed actually this really cool device. It's, I can share a video later. But it's an articulating sled that connects to the remotely operated vehicle. And it allows the vehicle to conduct a survey. So you can imagine it flies over a constant altitude. But then regardless of how, with the bathymetry, that's what the bottom of the ocean. So for example, now you're coming up against the wall, the sled will articulate itself. So the sensing is always pointed directly at the seafloor. And so that allows you to get continuous surveys regardless of what the topography is doing underwater. And with LIDAR imagery and sonar, you get very high resolution data. And so you can start describing species to the genius level using imagery. Cool. And then by returning to those points, you're able to track how you know things evolve over time. And so that's something we do and Those, that's one type of information that we gather and bury those images and videos that we collect are one of the biggest, I guess, databases that we have is those videos that these vehicles collect. And we have also some projects going on here now to expose some of that information and make it bring it to a format where you know, it's right for automation. And so so that's one type of data, then we have two autonomous vehicles that also carry those deep sea vehicles. So also geared towards mapping as a primary task. And they also carry these big sonars, and are able to do the surveys along the sea bottom, at depth, and retrieve, you know, high resolution maps of certain areas. And so that's another type of data that we collect. And then, in addition to that, we also have what we refer to as oceanographic sensors. So most typically, there's going to be sensors that collect temperature, salinity,

you know, that's how salty it is. Right? Correct. Second one, salinity,

salinity, correct. And the way Yeah, so that's kind of like your, your basic, but then you have also specialized sensors that are able to tell you the concentration of certain nutrients in the ocean water, for example, like nitrogen, nitrates, sensors, things like that. And then we also have even more specialized sensors that are able, for example, to sense the type of bioluminescence. So they have a chamber that past Yeah, so so you can see how much bioluminescence occurring in the body of water that you're traveling through. And so that's another type of

does that mean like an algae will produce light at night? Or something? I said analogy, or would it be like fish in a really deep ocean? Or both for?

Yeah, so they bioluminescence is light emitting organisms. And so that actually happens in a very wide range of species across the entire ocean. So it's pretty ubiquitous. And we have a lab here that studies, you know, how it happens. And what are the evolution pathways that lead to different types? That's really cool. Yeah. So so that's another type of, you know,

is it often in deep sea animals? Or do you see it in like surface algae? Or like, I don't know if like the ocean lights up at night? With algae? I could imagine that. But I wonder if it's true. No,

it is true. So larger organisms that that have bioluminescence are typically found deeper. And they use bioluminescence for various reasons, it could be for attracting a mate for trying to capture prey for deterring prey. And you see different patterns and different colors being used for different purposes. In the shallower water, there are many types of algae that have bioluminescence, for different reasons. And we actually have a project going on here to try and identify what type of allergy you're observing just based on the bioluminescence patterns. So yeah, so it's actually pretty ubiquitous in the ocean and happens in all kinds of

just out of curiosity, like, I don't really know anything about this, but why so I can understand animals having bioluminescence? Because they are, like, as the main reasons you've mentioned, hunting, or meeting or something like this, like it's beneficial for those reasons. But plants. I can't like algae is a plant to me. And I can't understand like how that would affect like, if there's one algae and it has a beautiful glow, it doesn't probably help that algae meeting with the other one, or maybe it's some reactive. What's the what's the reason why algae has bioluminescent glows?

Well, I don't have a straight answer. There's

there are probably a few. It could also be for prediction avoidance. If they all fluoresce all at once,

I guess it looks like we are waste or something at some stage.

If you try to imagine trying to capture one little particle, but suddenly, a light show blows up in front of you. I think it would be pretty hard to focus just on one single cell. But I'm not sure that's really the reason I want to get back into that

being some sort of thing. It's avoiding predators. I just intuitively I don't I don't have a good model for why that would be the case. And it's fascinating that that exists.

But right, yeah, yeah. And so Steve haddock, Dr. Steve had a career in MBARI. He leads research here on bioluminescence. And so we can go ahead and look up services research and probably get some answers. But he's, he's great.

So, those sensors to your bioluminescence sensors, and you mentioned a whole bunch of other ones so salty and temperature and different nutrients correctly. So those are the kinds of things you're collecting data about. And I guess, also the video one. So if you if you see an algae bloom, what kinds of things are you trying to sense about that, I suppose the nutrients is how salty it is the temperature, but then also maybe video of the event, and then or

Well, yes, for a biological shark for studying those type of microscopic organisms, we do have some imagery based payloads that we use in order to try and identify species.

So you mean like various cameras, camera setup, or something that you include on the robot. So you have your various payloads that have various sensors that you might include on your robots,

okay. And in addition to that, we also have the ability to acquire water samples autonomously at sea. And so we have a whole lab here, that's actually, that's their focus, and they've developed a payload on the environmental sample processor. And this is actually probably the most advanced type of it's not really a sensor, but it's more like a payload we refer to it, it's able to take in 60 water samples. So you can imagine some kind of like, a system that has an intake and is able to filter water, while the vehicles deployed at sea. And then also has some automation that's built in to this payload, to, you know, use the right reagents in order to fix fixate that, that sample. So it doesn't continue to change after you've filtered the water. And then that system also how that would

be like if you had some sort of bacteria in it, or something that were like continued to do, whatever. So it like, you'll basically sterilize everything or kill everything in it. So you can look at its components. And then you can easily subtract that reagent out when you are doing your tests on it. So you know, kind of your baseline, and you can see what it was at the time. Ah,

exactly correct. And then these payloads also have some analytical modules that are able to tell you things about the sample that you just acquired at sea. Cool. And so at the extreme case, and this is still hasn't been miniaturized to the point where it runs on a vehicle, you can run this type of sample and actually target specific genes. So do almost like a genomic analysis on the sample that you just acquired, and radio back to shore.

What are the genes of what is it literally genes of something? Are you like getting an algae sample and looking at it streams? Or what is it the what? Oh, it's okay. So it's an algae that you're synchronizing effectively. That's super cool.

Yeah. And then that allows you over time and space to see, you know, what was the? What was the community, the microbial community? What was it looking like? And over time, how is how has it evolved? And that, you know, is, is really useful for research and understanding how things change over time and with conditions. So as conditions change, how does the microbial community react, but also, it's very useful for monitoring. So you can example for example, you can have, you can imagine seeing a system like this deployed somewhere, and looking for a certain species of algae that's harmful for the environment, because it produces some toxin. And that's kind of like an early warning system. So again, geared toward not only doing research, but also conservation and resource management. So that's another another piece there. And so, you know, that generally, that payload kind of personifies, I guess, one of the major themes or research that have been going on here at the Institute, which what we refer to as taking the lab, to see, and being able to do sample processing, and do as much of the analysis that we can at sea and inform the vehicle autonomously, on how to proceed. And so, taking the lab to the ocean to the sea is has been a major theme here. And the type of development is also you know, it's always geared to if you if you could do it here at sea or on a ship, how can we take that same analysis and put it on a platform and so Oh, this, this this water sampling code that it just described, for example, now we're at the point where we're adding these modules that are able to also analyze the samples and have the vehicle, do this type of analysis at sea, and radio the results back to shore.

Gotcha. Okay, so they radio, the radio the results back. So this is for like, one of those surface monitoring robots. So it'll kind of like stay at some depth, that's not very deep, collect some information. And then it goes in chills at the very surface in the water, and it'll radio back the information for you guys to analyze, or do something with? And probably that's how you communicate with it for like, send it commands or something, as well, right?

So yeah, so the vehicles actually, they can also use on the sensory inputs to inform their, you know, actions. So our planning algorithms, for example, that look at sensor input, and decide how to steer the vehicle autonomously, for example, in order to try to stay with some kind of maximum concentration, where you know, you're sensing where most of the algae is, or where the highest concentration of algae is. And you can use optical sensors, to try to see how much chlorophyll is in the water using fluorescence. And so then you can use this information and driving the vehicle to do kind of like, you can imagine a gradient climbing algorithm that takes a vehicle from a, you know, an edge and drives it into center of the patch. And then when it reaches the center of patch, it will trigger a water sample. So that's something that we do here pretty typically. And then, in addition to that, I guess you mentioned communication. So yes, the vehicle surface periodically to surface with shore. But those type of applications, especially if you want to stay with a certain part of the water mass, meaning, let's say, because everything is moving in the ocean constantly, right, you've got currents carrying carrying these microorganisms. And if you lose that patch of water, and in order to go up to the surface and communicate well, when you come back down, you might be looking at our community. And so those type of applications really lend themselves well to multi vehicle constellations. And so that's been another focus here is this multi vehicle type of operations. And so in the example that we just discussed, you'll have one vehicle that is doing this graded climbing and looking for a maxilla. And then once it finds the highest concentration of chlorophyll, or whatever it is, it's looking for, it kind of just parks it underwater, and stays with that water mass and drifts. And the issue with that is, you know, after a while, you're not going to know what a vehicle is, you are not know you're not going to know what type of information it's looking at. And so a second vehicle will typically track this type of sampling vehicle, smart. And then one is at

the surface looking down and the other one is drifting with this algae Max.

Well, so that's one way to do it. And we also use autonomous surface vessels in order to track underwater assets. But we typically also have a second underwater vehicle that's profiling around it and tracking it, it's surfacing periodically, and it can relay information from the diving vehicle. And also, it gives the scientists more contextual data, because usually the second vehicle is kind of parked at one little part of the water column. And in order to get the full contextual data of what's going on, you also need a second vehicle in order to survey and get

the bird's eye view are the ones in the forest. And one is that the trees kind of thing.

Exactly. And so multi vehicle applications have been, you know, a main theme here. And I guess that kind of leads us toward maybe talking a little bit about the sim. Yeah,

one sec. Just before we go into that, what are these vehicles look like? So specifically talking about the surface monitoring ones where we're looking at algae, right? What are the what are the robots look like?

Yeah, so typically, they're kind of torpedo shaped vehicles. That's the most efficient way. And the vehicles that we work that I work with, specifically are kind of small size, so they're probably two to two and a half meters long, depending on the type of payload that they have. And the diameter is about 12 inches. And there it basically looks like torpedoes, I can show you A picture here maybe? Sure.

I'd love to talk a little bit about how they work and then get into the SIM stuff. Because the sim stuff is very interesting. For sure.

So this is a picture of one of our vehicles, those are test class long range EVs. So, like I mentioned, these are upper water column vehicles, they're pressure rated for about 300 meters. And what's special about them is really their endurance, we decided to

pretty much, yeah, if you ever seen a picture of it there, then it looks pretty much like that with a bit with a mask on top, and that's our communication antenna. Yeah, so go ahead, stop sharing it. But so that's the long end up now. I guess, like I mentioned, we embark has really been on the forefront of development of these platforms. And so on that vehicle that I just showed that this class long SUV has been developed and borrowed from scratch. And it's also manufactured here, and operated here. And so everything about that vehicle was designed here in house, these vehicles are special, they're special in their capacity for their high endurance vehicles, meaning they can cover about 1500 kilometers. And stay at sea for say, up to two to three weeks, which is unusual for vehicles at that size. Especially for ones that have propeller and they're able to thrust on their own. There are other types of vehicles that don't have thrusters and have longer endurance. But this vehicle is very special and unique. And that's capacity to stay up there.

So it doesn't do any, it basically you have a battery, and that battery will last for two to three weeks. And that dictates how long you can do it doesn't do any power generation or like go up to the surface and have solar panels fold out or

something. But it does. I mean, the power management system is very efficient, efficient. Yes, every every aspect of that vehicle is designed is really geared toward efficiency from the shape to the tail cone and how you know, the the hydrodynamic flow, and how water passes around it. It's going to set to minimize drag. And this vehicle specifically is also special because it can change its buoyancy. Meaning it most people that put very expensive pieces of equipment in the ocean, they make them buoyant. So if the agent stops working, we'll come back up. Well, this one is able to actually change its buoyancy at sea and fly neutral. And that actually gives you a huge efficiency boost, because you're not pushing against. Yeah, this upward force. And so then, you know, comes the question, okay, if something does go wrong, how do you manage that, and so their safety and power management are kind of the heart of this vehicle. And so both both have, you know, systems that are designed specifically in order to optimize the routers, the vehicle powers off systems automatically when it doesn't need them, even including extra readers. So it's very smart management on board. And, you know, when you you know, insurance in general, it's kind of death by 1000 cuts, right? Try to optimize around each parameter, eventually, you get a system that is able to persist and be out there for those type of durations. And again, the requirements for those durations come back to the original processes that we've discussed kind of in depth upon not intended.

So many ocean ponds are possible for sure. So with this, when it adjusts its buoyancy, the way it does that is it takes on water, right, like so it will have little cavities or something in it, or how does it work?

Yeah, well, actually. So our vehicle doesn't take in water, it uses oil. And so it can pass oil into a bladder that's external to the sealed compartment. And by doing that, so if you're taking oil from the sealed compartment, and pushing it out to a bladder that can inflate, you're actually changing the volume of the vehicle without changing its mass. And by definition, that makes it more buoyant. And when you want to become less buoyant, you just push the oil back into the seal compartments. And that deflates the bladder. And the vehicle

then becomes less of a thing. The volume changes in the mass stays constant and that changes the buoyancy of the correct Is it is it a lot of energy to like compress the oil Remove it inside to the oil. What?

It's not oil, it's not cool. It's non compressible oil.

It's like some sort of vacuum thing to move it from one spot to another.

Yeah, we have a valve that opens and then a pump that sits inside the seal compartment and can push oil outside. And it's designed in a way that, you know, it can push against pressure, even at depth. And then there's a lot of also some safety built in there, you know, what happens if suddenly you can't push against the pressure. And so there are some valves that are set to close automatically and make sure that water never makes it back. In in case of a failure. So like I said, failure management is one of the big things. Exactly. So pretty much every aspect here. Yeah. Go ahead. So.

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