WASHINGTON — Shield AI, which started with a quadcopter capable of flying indoors in GPS-denied environments, now wants to advance its artificial intelligence and autonomy technology by buying a drone company that has caught the attention of the military.
Shield AI’s purchase of Martin UAV, maker of the V-Bat vertical take-off-and-landing unmanned aircraft system, became official Friday. Shield AI, known for its Nova quadcopter, has already worked closely with the Defense Department’s technology hub, the Defense Innovation Unit. The company, which wants to expand its DOD work, said it has raised more than $50 million in venture funding since 2015.
The military services, and particularly the Army, have evaluated Martin UAVs for years. The aircraft first made an appearance in Germany at the 2018 European-based Joint Warfighting Assessment. There it was directly compared to Shadow capability.
Army soldiers spent the better part of a year evaluating V-Bat’s capability as part of the FTUAS competition. The Army is expected to soon release a request for proposals and will then select a winner to build a first tranche of UAS.
Martin UAV was also chosen to build a prototype in a U.S. Navy competition for a future UAS; Marine Corps units are flying V-Bat as well.
Defense News spoke with Brandon Tseng, a former Navy SEAL who is Shield AI’s cofounder and chief operating officer, on July 29 about what the acquisition of Martin UAV will mean for his company and for V-Bat’s future.
This interview was edited for length and clarity.
How has your business evolved since its inception and why is buying Martin UAV a good move for Shield AI?
When I was starting Shield AI, I was talking to Navy SEALs, Army Rangers, Army Special Forces about a problem that I was pretty familiar with — clearing buildings of threats. And that was what led to Nova [quadcopter], but a lot more broadly, I was interested in bringing artificial intelligence and autonomy to the defense sector because my hypothesis was that it could be game changing on the battlefield, in terms of improving mission effectiveness and reducing risk.
I spoke to a lot of ground warfighters, infantry, special operations forces, I spoke to a lot of pilots, I spoke to a lot of general officers about their strategic problems. What became a very common thread was we have issues operating in high-threat, GPS-denied and communications-denied environments. From drone operators to F-18 pilots to Apache pilots, I really started to learn about this problem of integrated air defense systems and how that was becoming an increasingly more prevalent threat on the battlefield that was denying our ability to maneuver.
We built a quadcopter that can go inside buildings autonomously, without GPS communications, not to be a quadcopter company, but to show the department the power of AI and autonomy and the value it provides in high threat, GPS-denied, communications-denied environments. What it has always been about for us is getting our AI and autonomy stack on platforms of increasing strategic consequence. And so we talked about climbing the unmanned systems food chain.
What about V-Bat convinced you to pursue Martin UAV?
We first heard about Martin UAV, and the V-Bat, either late 2018 or early 2019. We heard it from a variety of different sources. We heard about it from investors that were familiar with our thesis and our plan of climbing the unmanned systems food chain. We had heard about it from customers, saying, “Hey, it would be fantastic. What do you think about Hive Mind on board something like the V-Bat?”
Both companies had to grow. And in basically, late 2020, early 2021, it was, “OK, we’re ready, we’ve got the investment and the investors behind us to execute something like this.” And now, which aircraft makes the most sense. And we’ve looked at all the aircraft, and not only in defense, but in the commercial space, and where everybody’s playing and have spoken to customers, to consultants, about the pros and cons of each aircraft. It just became increasingly evident that the unique hardware architecture of the V-Bat lends itself to extremely compelling capabilities. it’s just not a limited system. And there’s limitations about some of these other systems out there, that would have been more difficult.
What is your vision for V-Bat’s capability in the future when bringing your technology on board?
Our goal is to build the next-generation defense technology company and it doesn’t look like existing defense companies today. It is a company that has an AI and software backbone or core that is leveraged across these different platforms. It is a software-first mentality, an AI-first mentality, but at the same time, it matters which hardware you put it on. I do not want to discount the importance of hardware in the military and on the battlefield. But I think it is software and AI first, in terms of the capabilities that are really going to matter at the end of the day.
Then it comes to swarming, having these things operate in teams. The way that we think about it is it is very similar to the self-driving car industry. You probably heard Elon Musk talk about putting a million robo-taxis on the road to operate in a highly distributed manner. But first, you need a single, self-driving car that works. It’s very similar with Shield AI’s approach, it’s build the highly intelligent system, then scale it. Don’t scale out a bunch of unintelligent systems because you’re just going to get formation flight. You’re not going to get any real value or capability; you won’t if you don’t have intelligent systems. You need intelligent systems to unlock the concept of overmatch.
What does that look like? It is training these systems to be able to execute a variety of missions. And there’s a long list of missions from countering integrated air defense systems to reconnaissance to escort operations to sensor emplacement and so we’ve been working on the AI aspect of these mission sets for the past several years.
Last week, you acquired Heron Systems. What does that bring to the table?
We’ve leaned in heavily on using simulations that are coupled with reinforcement learning, and basically you design a mission and then you let the system train itself over and over and over and over again, which is what Heron Systems did with the [Defense Advanced Research Projects Agency] AlphaDogfight. It’s how open AI trains systems to play hide-and-seek. We are applying those same techniques to these unmanned systems. To me, one of the most exciting things about AI and autonomy is that application of reinforcement learning to train systems to do things.
A lot of people look at Heron as “Hey, they did that AlphaDogfight program,” which, yes, that is something we care very much about, the next-generation air dominance program. The system beat actual pilots, a bunch of F-16 pilots, it beat a bunch of other AI pilots from other companies as well, like the large primes lost to it. But what I think a lot of people sometimes lose sight of is actually a lot of what they’re doing will be synergistic to how we think about AI pilots and autonomy onboard Group 3 aircraft like V-Bat.
What if the Army doesn’t choose V-Bat for its first tranche of FTUAS to replace the Shadow UAS?
One of the reasons we acquired Martin UAV is because we believe they have the most compelling Group 3 aircraft on the market and so, ahead of almost everything we think about is that, more than we think about the programs that it’s competing in. It is what is going to delight the heck out of the customer.
Where else do you see Shield AI technology cropping up? I know you have a relationship with Textron for example. Could you be out at Project Convergence?
The core for us is going to be with the V-Bat and Martin UAV, and that’s the focus for us. There’s a lot of work to be done there. There are certainly applications. But as you know, you have to have focus, you have to channel your resources in a focused manner.