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Combat-Grade Autonomous Drone System

Autonomy Without Boundaries

Dead reckoning navigation. On-device AI detection. Visual homing that works when nothing else does. No cloud. No GPS. Full autonomy — on any Android phone.

Operators define the task. DroneDev executes the mission autonomously.

SYSTEM ARCHITECTURE
FC LINKMSP / MAVLINK
FAILOVERMULTI-LAYER NAVIGATION
VISIONON-DEVICE NPU
DroneDev companion computer mounted on a quadcopter
Android companion computer · USB-OTG flight control

The Mission Gap
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Modern battlefields and critical infrastructure zones share one vulnerability: GPS is fragile. Jamming, spoofing, or urban canyons can render a drone blind in seconds. Cloud-dependent solutions fail when connectivity drops. Radar is heavy, expensive, and detectable.

DroneDev closes this gap. It turns any Android phone into a combat-grade companion computer that replaces GPS, cloud, and radar — all running fully offline, on-device, in real time.


How It Works
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USB-OTG
Connect to any FC
Real-Time
Dead Reckoning Rate
Multi-Class
AI Detection Categories
0
Cloud Dependencies
01 / INPUTSPhone sensorsCamera · IMU · compass · AI vision
02 / FUSIONNavigation coreSensor fusion · AI navigation engines
03 / CONTROLFlight controllerMSP v2 · MAVLink v2 · RC stream

Plug the phone into your flight controller. DroneDev auto-detects the protocol — MSP or MAVLink — and begins enhancing your drone’s capabilities immediately. No configuration. No internet. No compromise.


Dead Reckoning Navigation
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When GPS drops, most drones drift or RTH blindly. DroneDev’s sensor fusion engine combines the phone’s camera, AI image processing, compass, gyroscope, and accelerometer to maintain precise position estimates. An advanced sensor fusion filter continuously corrects drift — keeping you on course when satellites fail.

On-Device AI Detection — Neural Network Inference
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YOLOv8s, a state-of-the-art deep neural network, runs entirely on the phone’s NPU. No cloud, no server — the neural network executes directly on the phone’s neural processor. Object categories are defined by training — customize detection for your operational needs. Intelligent tracking maintains object identity across frames. Detection coordinates are transformed to real-world positions via on-device spatial mapping — so you know exactly where each target is.

Visual Homing — Neural Network Azimuth Lock
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Wind pushing the drone off-course? DroneDev automatically locks onto a YOLOv8s-detected landmark on the horizon — a building, tower, or tree — and uses it as a visual azimuth reference. The deep convolutional neural network tracks the landmark in real time, keeping the drone dead-on course regardless of crosswinds. No user tagging — the neural network chooses and locks automatically.

Autonomous Patrols
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Configure search patterns — grid, spiral, creeping line, expanding square — and let the drone execute autonomously. Detection responses are programmable: take a photo, land, drop a payload, track-and-follow, or return home. Every photo is EXIF geotagged with GPS coordinates, detection category, and confidence.



Proven Architecture
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DroneDev isn’t a concept. It’s a working MVP tested on real hardware:

  • Modern Android phone with USB-OTG → INAV flight controller
  • ArduPilot 4.x+ with MAVLink v2
  • MSP v2 for INAV/Betaflight flight controllers
  • Dual-protocol auto-detection — no manual switching
  • Intelligent control loop for both protocols
  • Tested hardware platform with documented integration path

Built for Operators Who Can’t Afford Failure
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Whether you’re securing a perimeter, searching a grid, or navigating denied airspace — DroneDev runs when cloud-based solutions can’t. Everything executes on the phone. No data leaves the device. No connectivity required. Full autonomy, zero compromise.

Ready to See It in Action?

Schedule a live demonstration. See dead reckoning, AI detection, and visual homing on real hardware — in your environment.

Request Demonstration →