From modularity in Avionics Software to Modular Unmanned Hardware
The Russia-Ukraine war has seen hundreds of thousands of drones being used. Yet, the war has also shown how quickly drones can lose significance. The Turkish-made Bayraktar TB2 drones, for example, which were instrumental in countering Russian forces early on, lost their effectiveness as air defence systems evolved. Rapid adaptability is crucial for an unmanned system for its optimum utilisation. So, it is not just about drones and unmanned vehicles but keeping them relevant and scalable and adapting them to mission modes.
According to Axel Bååthe, Head of The Rainforest – Saab's accelerator and lung for transformative innovation – there is an effective way to solve this issue by developing modularity and flexibility to allow customers to adapt the needs of the aerial vehicle to the mission requirements. "I think we are already there with Gripen E when it comes to (adapting) the actual software in the platform. But at The Rainforest, we are looking at the next step - how do we allow modularity and flexibility in the hardware as well to tailor different types of platforms to different types of missions using the same core," he explains.
In the modern air domain, the rising costs of aerial vehicles continue to present a critical challenge for air forces. Traditionally, air forces have leaned heavily on large, manned platforms, investing in expensive, sophisticated technologies to achieve tactical advantage. However, this reliance on expensive, complex systems in an era of strained defence budgets is far from sustainable.
"I think, in a big conventional entity, you typically default to air defence via larger, very expensive vehicles, typically manned vehicles. But we at The Rainforest and Saab see a big potential to complement that with smaller, cheaper vehicles, which offer quite decent performance, are capable of flying in the entire subsonic envelope, but are unmanned and built with cheaper technology that enables scaling of assets much, much quicker and gives a competitive advantage to customers," he says.
But opting for unmanned vehicles is just the first step. Most users of unmanned vehicles are currently focussing on executing missions by relying on sensors. The future, however, belongs to platforms with elevated autonomy driven by breakthroughs in Artificial Intelligence (AI) and cognitive computing. Autonomous systems will not just have better self-protection but can also adapt dynamically to mission requirements, offering deployment flexibility, including the ability to operate unmanned systems in large numbers like never before.
"So, I think the first big transformation is the integration of unmanned vehicles into the big civilian airspace and being able to scale the airborne assets much quicker than the personnel required on the ground for the systems. I think that is something that most drones out in the air today are struggling with. Yes, they are unmanned, but they aren't at an autonomy level that allows you to scale the number of aircraft in the air much, much quicker than the personnel on the ground. So, I think that's the first technology leap we are looking at," Axel says.
Despite the advancements in manufacturing, developing cost-effective drones is still a work in progress. Everything from materials to assembly, sensors, and AI adds to the cost. "We tend to focus on the performance or the specific sensors or the AI system in the actual vehicle. But we are ultimately still in an environment where we need to be able to produce the physical hardware and develop that physical hardware to follow the laws of physics. There's no way around getting around the laws of physics. And we see a trend, in the air domain, that vehicles keep getting more and more expensive," Axel says.
The answer lies in constant research and innovation. "It's more and more difficult to break the cost curve. I think we are showing with Gripen at Saab we've always, as a resource-constrained country like Sweden, had to develop cost-effective solutions. And the next step there, I think, has a lot to do with taking in the modern ways of developing software into hardware design. We're talking about continuous integration, continuous deployment, automatic testing of the hardware, and using methods that develop hardware as software. So one example is additive manufacturing at large scale, where you have the hardware design tool that allows you to just input new software and you get out the new design that is, by AI, topology optimised, and I think we will see big, big revolutions here in the amount of flexibility in hardware that new methods such as additive manufacturing create. So that's what we're looking at here, in The Rainforest," Axel explains.