ADA²M autonomous drone

Collect useful environmental data without walking the whole property.

Small scale farmers cannot instrument every corner of a paddock, and spot readings from one weather station do not describe a field. ADA²M sweeps a predefined coverage route and logs measurements along it. The engineering problem is packaging: an airframe, a flight controller, a long range link, onboard compute and a sensor payload all have to fit inside a mass and power budget that does not move.

A compact autonomous stack, in the order the signal travels.

1. Flight pathA predefined coverage route over the target area.
2. Flight controlA SpeedyBee F405 V4 stabilises the aircraft and executes commands.
3. Onboard computeA Jetson Nano runs inference for in flight decisions.
4. PayloadTemperature, humidity and air quality measurements, logged along the route.

Airframe

Custom carbon fibre frame

Long range link

TBS Crossfire

Design tool

SolidWorks

Software

C++ and Python

Build the platform, then make it behave.

1. Package the flight stack. Design the carbon fibre frame around the propulsion, control and compute hardware rather than fitting the hardware to a stock frame.
2. Connect autonomy to flight. Integrate Jetson Nano inference with onboard decision making so the aircraft can act on what it sees.
3. Design for range. Use a TBS Crossfire link so control and telemetry survive the distance a coverage route needs.
4. Test in steps. Move from short hops to stability tuning before expanding sensor and autonomy capability, so one failure only has one cause.

Built inside a student lab, not on a bench alone.

ADA²M runs under Project Umbrella Labs, the student led research and development group I co-founded at UNSW. The lab works across autonomous UAVs, neural interfaces and agricultural monitoring, and runs its projects as rapid prototype, test, revise cycles.

projectumbrellalabs.com ↗

Airborne, and still being tuned.