NSD Lab

Where Ideas Become Evidence

Some questions are too new to solve from a slide deck. NSD Lab is where we explore emerging technologies through research, simulation, prototypes and real-world experiments, turning promising ideas into evidence before they become products, services or client capability.

We use the Lab to test assumptions, understand constraints and learn where new technologies genuinely create value.

Quadcopter drone hovering at sunsetDrone
Notebook page of eight rough interface sketchesSketches
Flock map view with drone positions and waypointsFlock map
Workbench with electronics and prototype hardwareHardware
Drone console interface conceptConsole UI

Research is how we learn before the stakes are real.

01 / ACTIVE RESEARCH

Agentic Authority Boundary

How far should autonomous reasoning be allowed to become action?

An architectural approach for governing how far autonomous reasoning is permitted to become operationally binding. Explored through formal modelling, executable rules, simulation and evaluation.

  • Formal model
  • Simulation
  • Prototype
  • Evaluation
Layered model of Intent, Plan, Action and Execution. The Action layer is the authority boundary, highlighted.IntentPlanActionExecutionAUTHORITY
Question
When may an agent’s reasoned plan become a binding operational effect, and under what controls?
Approach
A formal authority model, a reference implementation and experimental evaluation in simulation and real-world scenarios.
Outputs
Paper · Reference implementation · Patent application
Status
Paper complete / implementation next

Patent pending. The current patent application is personally owned by Richard Knuszka.

Current investigations

Current investigations

  1. Investigation 02. Status · Exploring

    Collaborative Autonomy

    Can multiple autonomous vehicles maintain a shared mission when communications or individual vehicles fail?

    • Simulation
    • Prototype
    • Field test
    Small drones flying together above a ridge at sunset

    What we’re testing

    • Distributed state and coordination
    • Task reallocation
    • Degraded communications
    • Peer confirmation
    • Mission continuity
    More about this investigation

    We are engineering a mission control approach that lets a flock of small uncrewed aircraft share one picture of a task, divide the work and adjust as conditions change, rather than being flown one by one.

    Flocks of mini drones in a confined space make an ideal test bed for coordination, safe separation and shared tasks. Operators set the mission and its limits, and the link to our Agentic Authority Boundary work defines what each aircraft may decide for itself. Ideas are tested in simulation first, then in controlled field trials.

    Email us
  2. Investigation 03. Status · Exploring

    Indoor Autonomous Flight

    How can small aircraft understand and navigate an indoor space without GPS?

    • Hardware
    • UWB
    • Simulation
    Close view of a small quadcopter used for hands-on UAV work

    What we’re testing

    • UWB positioning and indoor tracking
    • Real-time control
    • Calibration
    • Positioning confidence
    • Hardware in the loop testing
    More about this investigation

    UWB, or ultra wideband radio positioning, uses short radio pulses between fixed anchors and a tag on the aircraft to estimate position where GPS is unavailable or unreliable.

    This thread also covers onboard edge compute, dockable VTOL research and hardware in the loop testing, so software can be proven against real components before it flies. No results are published yet.

    Email us
  3. Investigation 04. Status · Experiment published

    Distributed AI at the Edge

    What happens when intelligent systems have limited compute, power and connectivity?

    • Edge compute
    • Experiment
    • Distributed AI
    Architecture diagram from the One Model, Many Machines experiment, showing one language model split across a MacBook Pro and a Mac mini

    What we’re testing

    • Distributed inference
    • Constrained compute
    • Intermittent connectivity
    • Latency
    • Edge architecture
    • Practical deployment limits
    More about this investigation

    We run modern AI models across several smaller machines rather than one large server, and measure what that means for speed, cost and reliability.

    The One Model, Many Machines series on Bench to Sky documents a real experiment on the bench, splitting one language model across two Macs and recording what worked, what did not and why.

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  4. Investigation 05. Status · Design study published

    Human Supervision of Autonomous Systems

    How does one person meaningfully supervise several autonomous machines without becoming another dashboard operator?

    • UX research
    • Prototype
    • Design study
    Drone console concept showing a flock map, mission status and per drone cards

    What we’re testing

    • Mission-level interfaces
    • Attention and workload
    • Exception-driven interaction
    • Confidence and uncertainty
    • Handover
    • Progressive disclosure
    More about this investigation

    A design study for a portable drone console, worked through in sketch rounds and scenario walkthroughs of a small flock, including take over and degraded moments.

    Two Insights pieces turn this evidence into a broader design argument.

Also on the benchApplied computer vision. Real-time object detection, low latency perception for autonomous systems, and swim and sports analytics. ExploringBench to Sky projects (opens benchtosky.com)

From research to capability

A real example, from question to impact

Research follows a continuous path, from questions through studies and evidence to prototypes and real-world capability.

Explore more research stories
  1. Question

    Can an operator supervise several autonomous drones without monitoring each one individually?

  2. Study

    Scenario walkthroughs of a three drone flock, including take over and degraded moments.

  3. Observation

    Taking over the whole flock penalised drones that were fine, and per drone detail competed for attention.

  4. Prototype

    A mission-level console concept with exception-driven drill down.

  5. Insight

    Show the mission before the machinery.

  6. Application

    Human-centred UI patterns for autonomous systems.

Bench to Sky

Our engineering incubator

Research becomes more useful when it meets real hardware. Bench to Sky is where we build, break, simulate and test ideas before they become claims.

It gives NSD a practical environment for exploring UAVs, robotics, AI, sensing, positioning, interfaces and autonomous systems.

Explore Bench to Sky
Engineering workbench with a drone, electronics and tools
  • Simulation + hardware
  • UAV / AI / Robotics
  • Edge compute + sensing

Latest outputs

Latest outputs

From investigation to real-world capability

Explore our latest thinking in Insights, or talk to us about a research-led project where emerging technology could create real value.