"The LORD roars from Zion … the shepherd watches, and what he sees he declares." — the Book of Amos
In the Bible, Amos was a shepherd called to be a watchman — scanning the horizon, seeing threats others missed, and speaking truth when it mattered most. That is exactly what this platform does: it watches across every domain, fuses what it sees, and orchestrates autonomous forces to protect and respond. The name isn't a coincidence.
Autonomous Mission Orchestration System
AMOS is a multi-domain command-and-control platform that enables small teams of human operators to supervise and coordinate autonomous robotic assets across air, ground, maritime, cyber, and space domains.
Instead of controlling individual robots, operators define mission intent and AMOS orchestrates assets, sensors, autonomy engines, and communications to execute those missions.
v0.5.6 — Open Core Release | merkuri.one/amos
Launch a fully simulated autonomous mission with one command:
git clone https://github.com/merkuriddg/amos-autonomous_mission_orchestration_system.git
cd amos-autonomous_mission_orchestration_system
./run_demo.shBrowser opens automatically. Login: commander / amos_op1 — watch the mission unfold in real time.
Demo Scenarios:
./run_demo.sh border_patrol— Sensor network detects border intrusion, drones and ground robots investigate, track, and report (default)./run_demo.sh swarm_recon— Drone swarm deploys into contested zone, adapts to jamming and battery loss, tracks high-value target./run_demo.sh disaster_response— Earthquake SAR: drones map damage, robots inspect structures, AMOS prioritizes rescue tasks
Each scenario runs ~2 minutes with timed mission events, autonomous coordination, and human-in-the-loop checkpoints.
 Mission Console |
 Mission Planning |
 Simulation |
 Telemetry |
 Integrations |
 Threat Predictions |
 Kill Web |
 Swarm Control |
 SIGINT |
 Wargaming |
Most robotics software focuses on controlling individual systems. AMOS focuses on coordinating autonomous teams.
- Multi-robot mission orchestration
- Autonomous swarm coordination
- Sensor fusion and autonomous cueing
- Human-machine teaming
- Resilient mesh communications
- Extensible plugin architecture
AMOS acts as the mission layer between robotics frameworks and operational applications — integrating mission planning, autonomy orchestration, sensor fusion, wargaming, and resilient networking into a single platform.
git clone https://github.com/merkuriddg/amos-autonomous_mission_orchestration_system.git
cd amos-autonomous_mission_orchestration_system
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
python3 web/app.pyOpen http://localhost:2600 — Login: commander / amos_op1
AMOS runs without a database (in-memory mode). For persistent storage:
bash db/setup.sh # creates MariaDB database, user, schema, seed data| Username | Password | Role | Domain |
|---|---|---|---|
| commander | amos_op1 | Commander | All |
| pilot | wings2026 | Pilot | Air |
| grunt | hooah2026 | Ground Op | Ground |
| sailor | anchor2026 | Maritime Op | Maritime |
| observer | watch2026 | Observer | All |
| field | tactical2026 | Field Op | All |
AMOS ships in two editions:
-
Open (
AMOS_EDITION=open) — Core C2 platform: 200+ API routes, map, assets, threats, EW, SIGINT, cyber, sensor fusion, mesh networking, voice commands, plugin system. Free and open-source. -
Enterprise (
AMOS_EDITION=enterprise) — Full platform: 300+ API routes. Adds cognitive engine, NLP mission parser, Monte Carlo wargaming, swarm intelligence, kill web, ISR/ATR, effects chain, space domain, human-machine teaming, COMSEC, TAK/Link 16/STANAG integrations, and more.
See ENTERPRISE.md for the full comparison and licensing.
Applications
Mission Packs • Analytics • Operator Tools
▲
│
AMOS Platform
Mission Orchestration • Autonomy Engines • Swarm Coordination
▲
│
Integration Layer
ROS2 • MAVLink • TAK • MQTT • DDS • Link-16
▲
│
Assets & Sensors
Drones • Ground Robots • Maritime Vehicles • Satellites
amos/
├── web/ — Flask app, routes, templates, simulation engine
├── core/ — Data model, adapters, COMSEC, geo utilities
├── services/ — 48 autonomous subsystems
├── integrations/ — 23 protocol bridges (incl. DimOS bipedal robot bridge)
├── config/
│ ├── buildings/ — Building JSON floorplans (Alpha Compound, Embassy Bravo)
│ └── ... — Platoon config, theater locations, drone reference DB
├── examples/ — Demo scenarios + quickstart code samples
│ ├── border_intrusion/ — Border patrol demo
│ ├── swarm_recon/ — Swarm reconnaissance demo
│ ├── disaster_response/ — Earthquake SAR demo
│ └── quickstart/ — "Hello AMOS" API examples (Python + curl)
├── plugins/ — 19 plugins (adapters, mission packs, examples)
│ ├── adsb_adapter/ — ADS-B aircraft surveillance
│ ├── aprs_adapter/ — APRS amateur radio position tracking
│ ├── atak_adapter/ — ATAK/TAK blue force & CoT
│ ├── ais_adapter/ — AIS maritime vessel tracking
| ├── dragonos_adapter/ — DragonOS/WarDragon SDR sensor platform
| ├── sdr_adapter/ — Unified SDR (SDR++ / SigDigger / DragonOS)
| ├── remoteid_adapter/ — OpenDroneID / FAA RemoteID drone identification
| ├── cot_adapter/ — Cursor-on-Target XML ingest (UDP multicast + TCP)
| ├── zmeta_adapter/ — ZMeta v1.0 ISR metadata (UDP ingest + egress)
│ ├── meshtastic_adapter/
│ ├── px4_adapter/ — PX4 MAVLink autopilot bridge
│ ├── ros2_adapter/ — ROS 2 middleware bridge
│ ├── patrol_mission/ — Patrol mission pack (linear, orbit, sector sweep)
│ ├── search_rescue_mission/ — SAR mission pack (expanding square, parallel track)
│ ├── perimeter_security_mission/ — Perimeter defense (overwatch, tripwire zones)
│ ├── example_sensor/ — Reference sensor plugin
│ └── example_mission_pack/ — Reference mission template
├── sdk/ — Developer SDK (Python package + docs)
│ ├── python/amos_sdk/ — Installable SDK (contracts, helpers, testing)
│ └── docs/ — Plugin tutorial, contracts ref, integration patterns
├── tools/ — CLI tools (plugin scaffolding)
├── demo/ — Legacy demo scenarios
├── db/ — MariaDB schema + setup script (36 tables)
├── tests/ — 537 automated tests
└── docs/ — Architecture, SDK, simulation, API docs
Core Platform — 25 simulated assets (air/ground/maritime), 22 threats, C2 console with Leaflet map, digital twin dashboard, AWACS view, field 3D view, EW/SIGINT/cyber ops, swarm formation control, HAL autonomy engine, voice commands, contested environment simulation
Kill Chain & Readiness — F2T2EA kill web with human-approval gate, dynamic ROE posture, AI threat prediction, battle damage assessment, supply logistics
Wargaming — 1000+ iteration Monte Carlo simulations, Markov chain attrition modeling, 5 strategies × 3 tempos
Swarm Intelligence — Reynolds flocking physics, 6 emergent behaviors, task auction protocol, self-healing formations
ISR/ATR — Automatic target recognition, pattern-of-life analysis, change detection, prioritized collection
Effects Chain — Multi-domain strike orchestration (Cyber → EW → SIGINT → Kinetic → ISR), 5 pre-built templates
Space Domain — 9 orbital assets, Keplerian propagation, SATCOM link budgets, JADC2 mesh
Human-Machine Teaming — 5 autonomy levels, trust calibration, workload/fatigue assessment, adaptive delegation
Drone Reference DB — 105 drone entries (93 commercial via DroneCompare CC-BY-4.0, 7 military/tactical, 5 adversary), serial prefix lookup, RemoteID enrichment, counter-UAS context, searchable UI
CQB Operations Console — Full indoor mission planning and execution UI. Select buildings, generate clearing plans, assign assets, execute missions with real-time room clearance tracking. Threat intel overlay shows hostiles, IEDs, hostages, and civilian contacts from building intelligence and live perception fusion
3D Tactical Viewer — WebGL-rendered multi-story building viewer with floor isolation, color-coded room clearance status, asset position markers, threat icons, and SLAM occupancy grid overlay. Orbit/zoom/pan camera controls for full situational awareness
CQB Formations — 6 meter-scale tactical formations (STACK, BUTTONHOOK, CRISSCROSS, BOUNDING_OVERWATCH, PERIMETER, CORRIDOR) for close-quarters battle, dual lat/lng + local meter-coordinate modes, integrated with swarm orchestrator
Bipedal Squad Seeds — Environment type abstraction (outdoor_open, outdoor_urban, indoor_cqb), extended asset state model (posture, stance, manipulation, cover, fatigue, indoor position), indoor positioning data model for GPS-denied CQB ops
Building Data Model & Indoor Positioning — Per-structure JSON floorplans with rooms, doors, windows, stairwells, wall materials. Adjacency graph, BFS pathfinding, LOS queries, room clearing status. Multi-source indoor positioning (SLAM/UWB/IMU fusion) with per-asset tracking and lat/lng bridge for GPS-denied operations. Ships with 2 demo buildings: Alpha Compound (3-story) and Embassy Bravo (2-story diplomatic compound with threat intel)
CQB Room Clearing Planner — Autonomous mission planning for close-quarters battle: 6 CQB task types (BREACH, CLEAR, HOLD, SECURE, EXTRACT, STACK) with role assignment (point, number_2, cover, rear_security). Generates phased clearing plans from building models with dependency chains, reinforced door detection, and objective room targeting. CQB-specific ROE (hostage room restriction, fratricide prevention, CQB autonomy tier, range limits)
DimOS Bridge — Command-and-control integration for bipedal humanoid robots via the DimOS autonomy framework. Maps CQB task plans to robot navigation, manipulation, and perception primitives. Supports real robot connection (WebSocket) and standalone simulation mode. Configurable via DIMOS_ENDPOINT in .env. Manage from the Integrations page or CQB Ops console
System-of-Systems Dependency Map — Interactive D3.js force-directed graph showing every AMOS subsystem and how they connect. DB-backed nodes and edges with full CRUD. SWaP-C+ weighted scenario engine: 9 built-in weight dimensions (Risk, Reliability, Latency, Cost, Size, Weight, Power, Attrition, Geography) plus unlimited user-defined custom weights stored as JSON. Scenario planner lets operators save named weight-override sets, evaluate mission rollup scores (success probability, max risk, critical path latency, SWaP burden, Human Exposure Index, terrain sensitivity), and compare alternatives side-by-side. Red Team mode simulates node failures with cascading downstream impact visualization. Bush trail highlighting traces signal chains (CQB Assault, Sensor-to-Shooter, Resilience Backbone, Human Decision). Phase-band layout (Left of Bang → The Bang → Right of Bang) with node coloring by risk gradient in scenario mode, edge thickness by confidence, and drag-to-position persistence
Perception Fusion — Fuses detections from multiple indoor assets into a unified threat picture. Multi-sensor correlation (visual, thermal, LIDAR, acoustic), persistent track management, SLAM occupancy grid aggregation, and bidirectional intel forwarding to/from robots
Squad Supervisor — Autonomous squad mission orchestrator. Creates, plans, and executes supervised CQB missions with asset assignment, reserve management, formation control (STACK, LINE, WEDGE, DIAMOND, ECHELON, BOUNDING_OVERWATCH), contact handling, automatic re-tasking, and after-action report generation
Mesh Networking — MANET with 7 frequency bands, Dijkstra routing, frequency hopping, store-and-forward queuing
| Guide | Description |
|---|---|
/api/docs |
Interactive Swagger UI — auto-generated OpenAPI 3.0 docs for all routes |
/api/v1/openapi.json |
Machine-readable OpenAPI 3.0 JSON spec |
/mobile |
Mobile / Tablet Field Operator UI — touch-friendly responsive view |
docs/platform/ |
System architecture, simulation guide, API versioning |
docs/platform/AMOS_Plugin_SDK.md |
Plugin SDK — build asset adapters and integrations |
docs/platform/INTEGRATION_GUIDE.md |
Integration bridge development |
sdk/docs/PLUGIN_TUTORIAL.md |
Step-by-step plugin building tutorial |
sdk/docs/CONTRACTS.md |
Data contract reference (events, types) |
sdk/docs/INTEGRATION_PATTERNS.md |
Bridge architecture and patterns |
sdk/python/README.md |
SDK quickstart and API reference |
docs/hardware/DRAGONOS_SETUP.md |
DragonOS / WarDragon SDR integration guide |
docs/hardware/ZMETA_SETUP.md |
ZMeta ISR metadata integration guide |
ENTERPRISE.md |
Enterprise edition features and licensing |
SECURITY.md |
Security policy and vulnerability disclosure |
CONTRIBUTING.md |
Contribution guidelines and code style |
TRADEMARK.md |
Trademark policy and usage guidelines |
- Backend: Python 3, Flask, Flask-SocketIO
- Frontend: Vanilla JS, Leaflet.js, CesiumJS, WebSocket
- Database: MariaDB (optional — runs in-memory without it)
- Testing: pytest (537 tests), GitHub Actions CI (Python 3.11 + 3.12)
- Integrations: MAVLink, CoT XML (send + receive), TADIL J, ROS 2, MQTT, DDS, Kafka, VMF, STANAG 4586, ADS-B, APRS, AIS, RemoteID, LoRa/Meshtastic, NMEA, DragonOS/WarDragon SDR, SDR++, SigDigger, ZMeta ISR Metadata, DimOS (bipedal robot bridge)
- Security: AES-256-GCM encryption, HMAC, key lifecycle management
python3 -m pytest tests/ -v --tb=short537 tests across route, service, and contract layers. CI runs on every push via GitHub Actions.
Build your own AMOS plugins with the scaffolding tool:
python3 tools/create_plugin.py my_sensor --type sensor_adapterSupports 6 plugin types: asset_adapter, sensor_adapter, mission_pack, planner, analytics, transport
See the Plugin Tutorial for a step-by-step guide, or browse plugins/example_sensor/ for a reference implementation.
The SDK also provides typed data contracts and a test harness:
pip install -e sdk/python # install AMOS SDK locallyfrom amos_sdk import PluginBase, SensorReading
from amos_sdk.testing import PluginTestHarnessSee SDK README and Data Contracts for full reference.
AMOS Open Core is free and open source under the Apache License 2.0.
Enterprise modules are available under commercial license from Merkuri LLC. See ENTERPRISE.md.
AMOS™ and Autonomous Mission Orchestration System™ are trademarks of Merkuri LLC. Use of these names in commercial products or services requires written permission. See TRADEMARK.md for the full policy.
All contributions grant Merkuri LLC rights to use contributions commercially.
AMOS is a research and development platform. See SECURITY.md.
AMOS is built for the robotics, defense, and autonomous systems community. Here's how to contribute:
- Build a plugin — Use
tools/create_plugin.pyto scaffold a new asset adapter, sensor, or mission pack - Add an integration — Connect a new protocol or hardware platform (see
integrations/for examples) - Improve docs — Tutorials, API examples, deployment guides
- Write tests — Expand coverage across route, service, and contract layers
- Try a demo — Run
./run_demo.shand explore the platform
See CONTRIBUTING.md for guidelines.
Autonomous systems are rapidly evolving, but they remain fragmented. AMOS provides the mission operating system that allows autonomous systems to operate as coordinated teams.