Setup Development Environment

Before writing drone AI code, you need a proper development environment. This lesson walks you through installing Python tools, connecting to a simulator, and running your first autonomous flight.

Environment Architecture

Installation Guide

# Step 1: Create virtual environment
python -m venv drone-env
source drone-env/bin/activate  # Linux/Mac
# drone-env\Scripts\activate   # Windows

# Step 2: Install DroneKit
pip install dronekit
pip install dronekit-sitl

# Step 3: Install MAVProxy (for command-line monitoring)
pip install pymavlink mavproxy

# Step 4: Install additional libraries
pip install numpy matplotlib

# Step 5: Start SITL simulator
dronekit-sitl start --model quad --instance 0

Connecting to SITL

First Autonomous Flight

MAVProxy Ground Station

Using AirSim for Visual Simulation

Project Structure Template

Connection Helper Module

Hands-On Project: Build a Complete Mission Script

Summary

• DroneKit-Python is the primary API for drone control via MAVLink
• SITL provides a simulated flight environment for testing
• MAVProxy offers command-line monitoring and control
• AirSim adds visual simulation with Unreal Engine (optional)
• Always test in simulation first before flying real hardware
• Use the connection helper pattern for reliable vehicle connections
• The development stack: Python code -> DroneKit -> MAVLink -> SITL/Firmware

You now have a complete foundation for building drone AI applications. Start with SITL simulation, master the APIs, then move to real hardware!