SmartNav

A modular microservices-based simulation system with an aerospace flight control frontend visualization.

Components

Backend Microservices

The system consists of the following microservices:

• Audio Service: Analyzes audio input (beats, pitch, waveform) and publishes events.
• Simulation Controller: Subscribes to audio events and routes commands to agents.
• Agents:
  • Robot Arm: Simulates robotic movement.
  • Lighting: Simulates environmental lighting.

Frontend Application (AeroNavSim)

A React-based frontend application (frontend/) that visualizes an autonomous aerospace flight control system. Features include:

Core Features:

• High-fidelity vector graphics simulation with HTML5 Canvas
• Real-time audio analysis using Web Audio API with Web Worker optimization
• Multi-Agent Reinforcement Learning with Q-Learning and coordination detection
• Physics-based movement using Cannon.js 3D physics engine
• System telemetry dashboard with live service status
• Combat/Training mode with different visual and behavioral modes

Developer Tools:

• Performance profiler (FPS, memory, render time)
• Dev tools panel with state inspector and network simulation
• Error boundaries with crash reporting
• Structured logging with filtering and export
• Keyboard shortcuts and command palette

Advanced Features:

• Training dashboard for RL metrics visualization
• Synthetic data generation (audio augmentation)
• RL backend WebSocket connection for external neural networks
• USD scene export for NVIDIA Omniverse integration
• 3D model viewer for CAD models and URDF files
• Data export (CSV, JSON, USD formats)

See frontend/README.md for detailed frontend documentation.

Communication

Backend services communicate using gRPC and ZeroMQ.

• gRPC: Used for service-to-service command and control.
• ZeroMQ: Used for low-latency event publishing (optional/future optimization, currently using gRPC streams or simple RPCs for simplicity in v1).

Prerequisites

Backend

• Docker
• Docker Compose

Frontend

• Modern web browser with ES modules support
• Python 3 or Node.js (for development server)
• Microphone access (optional, for real-time audio input)

Usage

Backend Services

1. Build the services:

   docker-compose build

2. Run the simulation:

   docker-compose up

Frontend Application

1. Navigate to the frontend directory:

   cd frontend

2. Start a development server (choose one):

   # Python 3
   python -m http.server 8000
   
   # Node.js (with http-server)
   npx http-server -p 8000
   
   # Node.js (with serve)
   npx serve -p 8000

3. Open http://localhost:8000 in your browser.

See frontend/README.md for more details.