BoTH 2: Drones

As jamming technologies rapidly evolve, drones increasingly operate in GNSS- and RF-denied   environments. They still need to carry out complex, multi-step tasks, such as reconnaissance and cargo delivery – or searching for a target in a large GNSS-denied area.

 

How might we develop low-cost drones (additional hardware cost of maximum EUR 300 per drone) that can carry out such sophisticated tasks?

Think upgraded sensors, swarming, map reading, dynamically identifying gaps in jamming – and of course any other insane ideas you might come up with.

As manufacturing of military drones is ramping up worldwide, defending against vast quantities of adversary drones is a likely scenario. Humans – with their limited numbers, need for extensive training, and comparatively slow reflexes – will likely present a bottleneck.

 

How might we design and deploy low-cost, fully autonomous anti-drone drones that could be deployed by a single operator?

Imagine designating a target for the drone and launching it within a few seconds, with minimal use of connectivity or additional hardware.

Bonus question: thinking a little bit ahead, how might we make the deployment and targeting of anti-drone drones completely automated?

A typical drone team consists of 5 people who carry out a variety of tasks: manage multiple drones (ISR, repeater drone, bomber, FPV), last-step drone assembly, communications and command. These jobs require highly specialised personnel.  It’s hard to hide teams that large in visual and RF spectrum. There are multiple ways of protecting them, such as separating the control centre from the launch site or having fewer teams in the field.

 

How might we enable operators to control multiple drones at the same time, doing substantially more with the same small team?

Think better human/machine interface (example: https://www.primordial-labs.com/) and AI; all other ideas are welcome!

In case of a rapid escalation of a conflict, Belgian Defence will likely face a shortage of skilled drone pilots for a vast array of tasks, from logistics and search-and-rescue to reconnaissance, counter-drone, and operations.While basic drone flying skills can be trained in a few hours, identifying recruits with the military mindset, training them in the necessary military knowledge (tactics, techniques, and procedures), and keeping their skills up to date is far more complicated.

 

How might we recruit and maintain a cadre of up to 1000 trained drone operators?

Think about new ways of popularising the hobby of drone flying. Further, keep in mind current bottlenecks such as expensive equipment, shortage of dedicated air space, limited supply of drones for hands-on training, and constraints of currently available drone simulators.

All companies active in the drone ecosystem face many common issues: from staying up to speed with regulations to constantly chasing the ever-accelerating technological innovation. How might we construct an effective drone ecosystem that would successfully tackle these and other challenges?

 

How (and by whom) would it be managed? Financed?

How would it keep being a useful tool for the entire ecosystem instead of slowly turning into yet another ineffectual industry “body” that only serves its own perpetuation? Show us your (business) plan.

We need to ensure scalability of the manufacturing capacity of the Belgian drone ecosystem to meet the needs of Belgian Defence (going from 2 000 units/year in peacetime to 100 000 units/year in conflict time). This means the available manufacturing capacity of the Belgian drone ecosystem needs to go up by two orders of magnitude. To attain this growth and maintain this capacity, a successful Dual Use approach is a likely path.

 

How would the Belgian drone ecosystem (combining private sector, academia, and Defence) need to be organised to become a competitive European actor for large-scale manufacturing contracts?

Think about – for example – pooling resources to substantially increase shared business development activity in the civilian and military space, and don’t forget other aspects (such as R&D, collective procurement, etc.) that might need to be coordinated. Recommended reading here.

To ensure scalability of manufacturing, ease of in-the-field updates and upgrades to drones, interoperability between components and systems, and creating a genuine competitive advantage for the Belgian drone ecosystem, taking a Modular Open Systems Architecture (MOSA) approach adopted by all ecosystem members may be the right answer.

 

How might the Belgian drone ecosystem – formalised only to a limited degree – define an inexpensive drone system (hardware, sensors, firmware, controller, software) in line with Modular Open Systems Architecture (MOSA) approach, and keep it up to date?

A successful project might include:

• A description of MOSA combining a sub-EUR 2 000 FPV attack system, a sub-EUR 10 000 ISR quadcopter system, and a sub-EUR 50 000 long-range attack system, including command and control, data management and the actual flying platforms.
• An overview of the process for creating the initial MOSA and ongoing review and improvement.

Note that while BELDEF will be giving input and feedback, as well as providing relevant technical knowledge, it will not be in the driving seat of creating MOSA.

Recommended reading here.

Currently available R&D budgets tend to focus on low-TRL research projects, leaving a gap for faster adoption of high-TRL research. For example, technologies that can be applied for cost reduction in the near term may be deprioritised in favor of frontier technologies such as quantum or AGI.

 

How might the Belgian drone ecosystem create and continuously evolve a shared technology roadmap in consultation with BELDEF?

A successful project might include:

• An example of a technology roadmap for drones with a 5-year horizon
• The process for coordination of R&D efforts with universities to ensure timely integration of fundamental research
• Infrastructure requirements for testing facilities
• Needs for knowledge sharing from Belgian Defence