Drone Show System — ArduPilot SITL + Skybrush Integration

A complete drone show orchestration system built on ArduPilot with Skybrush-compatible integration, featuring 3D real-time visualization, synchronized multi-drone choreography, and fleet scaling to 150+ drones.

Demo Video

Watch the full demo video here — Real-time 3D visualization showing 3 drones performing synchronized formations (Triangle, Line, Vertical Stack), live telemetry (GPS, battery, altitude, speed), Skybrush bridge integration, and the complete show workflow from preflight checks through choreography execution to RTL landing.

Features

Full ArduPilot SITL Simulation — Enhanced simulator with complete sensor emulation (GPS 3D fix, 14 satellites, battery model, EKF status, MAVLink telemetry)
Skybrush-Compatible Bridge — HTTP REST API + WebSocket server implementing Skybrush Live protocol endpoints for drone discovery, show upload, execution, and monitoring
3D Real-Time Visualization — Three.js WebGL dashboard with orbit camera, drone models with spinning rotors, LED glow effects, flight trails, and formation tracking
Synchronized Choreography — 6-segment demo show: Triangle, Rise, Line, Vertical Stack, Expanding Triangle, Finale — with per-drone waypoint sequencing
128-Parameter ArduPilot Configuration — Production-ready parameter sets covering EKF3, GPS/RTK, geofence, failsafes, motor tuning, position controller, and flight modes
Fleet Scaling System — Automated parameter replication generating unique configs for 150 drones with GPS grid positioning and fleet manifests
Comprehensive Safety Stack — Layered failsafes (GCS loss, EKF degradation, battery cascade, geofence breach), emergency stop, preflight checklist
ESC & Sensor Calibration — Automated scripts for accelerometer, gyroscope, compass, barometer, and ESC parameter deployment

System Architecture

┌─────────────────────────────────────────────────────────────┐
│              3D Visualization (Three.js WebGL)              │
│         Real-time drone positions, trails, formations       │
│                    http://host:5000/viz                      │
├─────────────────────────────────────────────────────────────┤
│                   Skybrush Bridge Server                     │
│          HTTP REST API (15+ endpoints) + WebSocket           │
│                      Port 5000                               │
├─────────────────────────────────────────────────────────────┤
│                 Drone Show Controller                        │
│    Orchestration · Choreography · Safety · Monitoring        │
├───────────┬───────────┬───────────┬─────────────────────────┤
│  Drone 1  │  Drone 2  │  Drone 3  │  ... Drone N            │
│   :5760   │   :5770   │   :5780   │  :5760+(N-1)*10         │
│  SYSID=1  │  SYSID=2  │  SYSID=3  │  SYSID=N               │
└───────────┴───────────┴───────────┴─────────────────────────┘
      Enhanced SITL Instances (MAVLink over TCP)

Quick Start

Prerequisites

# Python 3.10+ required
python3 --version

# Clone the repository
git clone https://github.com/Muhammaduazir69/drone_show_ardupilot_sitl_skybrush.git
cd drone_show_ardupilot_sitl_skybrush

Setup

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install pymavlink MAVProxy dronekit dronekit-sitl
pip install flask flask-socketio aiohttp websockets geopy numpy scipy requests pyyaml jsonschema

Launch

# Option 1: Master launch script (starts everything)
./scripts/launch_all.sh 3

# Option 2: Manual launch
source venv/bin/activate

# Terminal 1 — SITL (3 drones with full sensor simulation)
python3 scripts/enhanced_sitl.py --drones 3

# Terminal 2 — Skybrush Bridge + Dashboard
python3 scripts/skybrush_bridge.py

Open in Browser

Page	URL	Description
3D Visualization	`http://127.0.0.1:5000/viz`	Real-time 3D drone view with formations
Control Dashboard	`http://127.0.0.1:5000/`	Telemetry panels + controls

Run the Demo Show

Open http://127.0.0.1:5000/viz
Connect — links to all SITL drones
Preflight Check — validates GPS, EKF, battery, parameters
Load Show — loads 6-segment choreography
Arm All — rotors spin up
Takeoff — synchronized climb to 10m
START SHOW — executes formations (Triangle → Line → Stack → Finale)
RTL — all drones return home and land

Project Structure

├── config/
│   ├── show_config.json                  # Master show configuration
│   ├── drone_params/
│   │   ├── drone_show_base.param         # 128 ArduPilot parameters (base template)
│   │   ├── drone1.param                  # Drone 1 overrides (SYSID=1)
│   │   ├── drone2.param                  # Drone 2 overrides (SYSID=2)
│   │   └── drone3.param                  # Drone 3 overrides (SYSID=3)
│   └── show_params/
│       ├── geofence_show.param           # Geofence: 300m radius, 120m alt
│       ├── safety_show.param             # Failsafe chain configuration
│       └── rtk_gps.param                # RTK GPS + EKF precision tuning
│
├── choreography/
│   └── demo_show.json                    # 6-segment formation choreography
│
├── scripts/
│   ├── enhanced_sitl.py                  # Full-sensor SITL simulator
│   ├── drone_show_controller.py          # Core orchestration engine
│   ├── skybrush_bridge.py                # HTTP/WebSocket bridge server
│   ├── launch_all.sh                     # Master launch script
│   ├── launch_sitl.sh                    # SITL-only launcher
│   ├── launch_sitl_proper.py             # Python SITL launcher + tester
│   ├── launch_fleet_sitl.sh              # 150-drone fleet launcher
│   ├── mavproxy_multi.py                 # MAVProxy multi-drone manager
│   ├── param_replicator.py              # Fleet parameter generator
│   ├── esc_calibration.py                # ESC calibration deployment
│   ├── sensor_calibration.py             # IMU/compass/baro calibration
│   ├── preflight_checklist.py            # Pre-show GO/NO-GO validation
│   └── run_demo.py                       # Interactive demo runner
│
├── monitoring/
│   ├── dashboard.html                    # Telemetry control dashboard
│   └── visualization.html                # Three.js 3D visualization
│
├── logs/                                 # Runtime logs (git-ignored)
└── templates/                            # Show templates

ArduPilot Parameters

Base Configuration (128 parameters)

The drone_show_base.param template covers every parameter group required for drone show operations:

Category	Key Parameters	Purpose
EKF3	`EK3_ENABLE`, `EK3_GPS_TYPE`, `EK3_POSNE_M_NSE`, `EK3_SRC1_POSXY`	Navigation filter with GPS source, tuned noise for show precision
GPS/RTK	`GPS_TYPE`, `GPS_NAVFILTER`, `GPS_INJECT_TO`, `GPS_AUTO_SWITCH`	RTK injection, DGPS, blending for cm-level accuracy
Geofence	`FENCE_ENABLE`, `FENCE_TYPE=7`, `FENCE_ALT_MAX=120`, `FENCE_RADIUS=300`	Altitude + circle + polygon boundary enforcement
Failsafes	`FS_THR_ENABLE`, `FS_GCS_ENABLE=2`, `FS_EKF_ACTION`, `BATT_FS_*`	Throttle, GCS loss (SmartRTL), EKF degradation, battery cascade
Battery	`BATT_LOW_VOLT=14.0`, `BATT_CRT_VOLT=13.2`, `BATT_FS_LOW_ACT=2`	4S LiPo monitoring with RTL/Land cascade
Position	`WPNAV_SPEED=500`, `WPNAV_ACCEL=100`, `PSC_POSXY_P`, `PSC_VELXY_P/I/D`	Waypoint navigation and position hold tuning
Motors	`MOT_SPIN_ARM=0.1`, `MOT_THST_EXPO=0.65`, `MOT_THST_HOVER=0.35`	Throttle curve, spin ranges, hover estimate
Flight Modes	`FLTMODE1-6`: Stabilize, Guided, RTL, Loiter, Land, Auto	Show requires GUIDED (Skybrush), RTL (failsafe)
Safety	`ARMING_CHECK=1`, `RC8_OPTION=31`, `BRD_SAFETY*`	Pre-arm validation, emergency motor kill channel
Logging	`LOG_BITMASK=176126`, `LOG_FILE_DSRMROT=1`	Full telemetry logging for post-show analysis

Parameter Relationships

These parameters form interdependent systems:

EKF ↔ GPS: EK3_POSNE_M_NSE must match GPS accuracy — 0.3m for RTK, 1.0m+ for standard GPS
Motor ↔ Battery ↔ Failsafe: MOT_BAT_VOLT_MAX/MIN → BATT_LOW_VOLT → BATT_FS_LOW_ACT cascade
WPNAV ↔ PSC: WPNAV_ACCEL limits how aggressively PSC_VELXY_P can respond — tuned together for formation precision without oscillation
Geofence ↔ RTL: FENCE_ACTION=1 triggers RTL; RTL_ALT must be staggered across fleet to prevent collision

Show Choreography Format

Shows are JSON files with segments containing per-drone waypoints:

{
    "show_name": "Demo Formation Show",
    "total_duration": 180,
    "segments": [
        {
            "name": "Formation: Triangle",
            "duration": 30,
            "waypoints": {
                "1": [{ "lat": 47.397792, "lon": 8.545594, "alt": 15.0, "speed": 2.0,
                         "yaw": 180, "led_color": [255, 0, 0] }],
                "2": [{ "lat": 47.397717, "lon": 8.545494, "alt": 15.0, "speed": 2.0,
                         "yaw": 60, "led_color": [0, 255, 0] }],
                "3": [{ "lat": 47.397717, "lon": 8.545694, "alt": 15.0, "speed": 2.0,
                         "yaw": 300, "led_color": [0, 0, 255] }]
            }
        }
    ]
}

Demo Show Segments

#	Formation	Duration	Description
1	Triangle	30s	Equilateral triangle at 15m
2	Rise	15s	All drones climb to 25m
3	Line	30s	Horizontal line at 25m
4	Vertical Stack	30s	Stacked at 15/25/35m
5	Expanding Triangle	30s	Wide triangle at 20m
6	Finale	25s	Converge to center at 10m

API Reference

REST Endpoints

Endpoint	Method	Description
`/api/status`	GET	System status + all drone telemetry
`/api/drones`	GET	All drone positions and states
`/api/drones/{id}`	GET	Single drone detail
`/api/connect`	POST	Connect to SITL drones
`/api/preflight`	POST	Run GO/NO-GO checks
`/api/show/load`	POST	Load choreography file
`/api/show/start`	POST	Execute show (choreography only)
`/api/show/stop`	POST	Stop show + RTL
`/api/show/status`	GET	Current show phase + elapsed time
`/api/arm`	POST	Arm all drones
`/api/takeoff`	POST	Synchronized takeoff
`/api/rtl`	POST	Return to launch
`/api/land`	POST	Land at current position
`/api/emergency`	POST	Emergency stop (immediate land)
`/api/config`	GET	Get current configuration
`/api/params/upload`	POST	Upload parameters to a drone

WebSocket

ws://127.0.0.1:5000/ws

5Hz telemetry stream with all drone positions, states, battery, GPS, and show phase.

Scaling to 150 Drones

Generate Fleet Parameters

source venv/bin/activate
python3 scripts/param_replicator.py --num-drones 150 --columns 15 --spacing 5.0

This generates:

150 parameter files — each with unique SYSID_THISMAV (1–150)
Fleet manifest (fleet_manifest.json) — GPS grid positions for all drones
Fleet launch script (launch_fleet_sitl.sh) — starts all SITL instances

Grid Layout

 15 columns × 10 rows = 150 drones
 5.0m spacing between drones
 Each drone: unique SYSID + calculated GPS home position

Upload to Real Hardware

python3 scripts/param_replicator.py --upload 1 --connection /dev/ttyUSB0

Calibration Scripts

source venv/bin/activate

# ESC calibration (motor parameters)
python3 scripts/esc_calibration.py 3

# Sensor calibration (accel, gyro, compass, baro)
python3 scripts/sensor_calibration.py 3

# Pre-show checklist (GO/NO-GO)
python3 scripts/preflight_checklist.py 3

Enhanced SITL Simulator

The enhanced_sitl.py provides a full-featured ArduPilot SITL replacement with:

GPS simulation — 3D fix, 14 satellites, configurable HDOP/VDOP
Battery model — Voltage sag under load, current draw based on throttle, mAh tracking
EKF status — All flags set (attitude, velocity, position horizontal/vertical)
Physics engine — Takeoff, guided navigation, RTL with altitude hold, landing detection
MAVLink v1 — Full heartbeat, GLOBAL_POSITION_INT, GPS_RAW_INT, SYS_STATUS, VFR_HUD, EKF_STATUS_REPORT, ATTITUDE
Multi-client TCP — Multiple simultaneous GCS connections per drone

Transitioning to Real Hardware

Step	Action	Tool
1	Flash ArduCopter 4.5+ firmware	Mission Planner
2	Upload `drone_show_base.param`	Mission Planner / MAVProxy
3	Upload drone-specific params (SYSID)	`param_replicator.py --upload`
4	Accelerometer calibration (6-position)	Mission Planner
5	Compass calibration	Mission Planner
6	ESC calibration	`esc_calibration.py` or Mission Planner
7	Configure RTK base station	Mission Planner GPS inject
8	Set polygon geofence around show area	Mission Planner
9	Verify all failsafes trigger correctly	Manual testing
10	Update `show_config.json` with real GPS coords	Text editor
11	Switch connection strings from TCP to serial/UDP	`show_config.json`
12	Run preflight checklist	`preflight_checklist.py`

Tech Stack

Simulation: Custom Enhanced SITL with MAVLink TCP server
Communication: pymavlink, MAVProxy, dronekit-python
Server: aiohttp (async HTTP + WebSocket)
Visualization: Three.js r128, OrbitControls, WebGL
Orchestration: Python asyncio
Parameters: ArduCopter 4.5+ compatible .param files

License

MIT

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Repository files navigation

Drone Show System — ArduPilot SITL + Skybrush Integration

Demo Video

Features

System Architecture

Quick Start

Prerequisites

Setup

Launch

Open in Browser

Run the Demo Show

Project Structure

ArduPilot Parameters

Base Configuration (128 parameters)

Parameter Relationships

Show Choreography Format

Demo Show Segments

API Reference

REST Endpoints

WebSocket

Scaling to 150 Drones

Generate Fleet Parameters

Grid Layout

Upload to Real Hardware

Calibration Scripts

Enhanced SITL Simulator

Transitioning to Real Hardware

Tech Stack

License

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Name		Name	Last commit message	Last commit date
choreography		choreography
config		config
logs		logs
monitoring		monitoring
scripts		scripts
templates		templates
.gitignore		.gitignore
README.md		README.md

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Drone Show System — ArduPilot SITL + Skybrush Integration

Demo Video

Features

System Architecture

Quick Start

Prerequisites

Setup

Launch

Open in Browser

Run the Demo Show

Project Structure

ArduPilot Parameters

Base Configuration (128 parameters)

Parameter Relationships

Show Choreography Format

Demo Show Segments

API Reference

REST Endpoints

WebSocket

Scaling to 150 Drones

Generate Fleet Parameters

Grid Layout

Upload to Real Hardware

Calibration Scripts

Enhanced SITL Simulator

Transitioning to Real Hardware

Tech Stack

License

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