Project Plan: Gesture-Controlled Drone System¶

Demo 2: Gesture Recognition + Real Drone Integration¶

Claim¶

Gesture recognition with real drone integration using existing adapter pattern

Demo 2 Deliverables¶

Already Complete¶

Hand tracking system
Dashboard telemetry
Simulator adapter (AirSim/Gazebo)

In Progress¶

Gesture Recognition — Rule-based implementation on top of hand tracking
Command Translation — Gesture → adapter command pipeline
Real Drone Adapter — xFly SDK or DJI Tello (using same adapter interface)
Safety Layer — Signal-loss hovering, command validation

Demo 3 Deliverables (4 Weeks)¶

End-to-end system on real hardware (no simulator needed)
User calibration workflow (personalize hand tracking to individual users)
Flight data analysis (charts, playback, improvement suggestions)
Mobile PWA deployment
Performance optimization (latency <50ms target)

Blockers & Monitoring¶

Blocker	Status	Mitigation
Real drone SDK documentation	Tracking	Vendor support coordination
Adapter parity (AirSim ↔ Gazebo telemetry format)	Tracking	Standardize telemetry schema
Command latency optimization	Tracking	Gesture recognition + transmission + drone response

Roadmap Beyond Demo 3¶

Two-hand gestures (complex commands using both hands)
ML-based gesture recognition (TensorFlow Lite for ambiguous cases)
Voice feedback layer (drone announces state changes)
Multi-user gesture library (community-contributed gesture sets)

Technical Architecture¶

Adapter Pattern (Key Strength)¶

The same gesture → command pipeline works seamlessly for: - Simulator adapters (AirSim, Gazebo) - Real drone adapters (xFly SDK, DJI Tello)

This allows us to develop and test on simulators, then swap the adapter to real hardware without changing core logic.

Gesture Recognition Pipeline¶

Hand Tracking Input
    ↓
Gesture Recognition (Rule-based)
    ↓
Command Translation
    ↓
Adapter Interface (Simulator or Real)
    ↓
Drone Command Execution

Safety Features¶

Signal-loss hovering — Drone enters hover mode if connection drops
Command validation — All commands validated before execution
Latency monitoring — Target <50ms for end-to-end response

Timeline Overview¶

Demo 2
├── Gesture recognition (rule-based)
├── Command translation layer
├── Real drone adapter integration
└── Safety validation

Demo 3
├── End-to-end hardware testing
├── User calibration workflow
├── Flight data analytics
├── PWA deployment
└── Performance optimization

Success Criteria¶

Gesture recognition system deployed and tested on hand tracking data
Real drone adapter working with same command interface as simulator
End-to-end latency measured and optimized to <50ms
Safety features validated (signal loss, command validation)
Demo 2 successfully executed on real hardware
User calibration workflow completed for Demo 3
Analytics dashboard shows flight telemetry and performance metrics