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Installation Guide

Prerequisites

Before installing drone-pathgen, ensure you have the required system dependencies:

macOS (Homebrew)

brew install ompl eigen boost

Ubuntu/Debian

sudo apt-get update
sudo apt-get install libompl-dev libeigen3-dev libboost-all-dev

System Requirements

  • Python: 3.8 - 3.12
  • OS: Linux, macOS
  • Compiler: C++17 compatible (GCC 7+, Clang 8+)

Installation Options

Option 1: Core Library Only

For basic trajectory planning functionality:

# Using uv (recommended)
uv add git+https://github.com/u-k-g/drone-pathgen.git

# Using pip
pip install git+https://github.com/u-k-g/drone-pathgen.git

Option 2: With Visualization Support

For 3D visualization capabilities (adds Open3D dependency):

# Using uv
uv add "git+https://github.com/u-k-g/drone-pathgen.git[viz]"

# Using pip  
pip install "git+https://github.com/u-k-g/drone-pathgen.git[viz]"

Verification

Test your installation:

import gcopter_cpp as gc
import numpy as np

# Create API instance
api = gc.GCopterAPI()
print("✅ drone-pathgen installed successfully!")

# Test basic functionality
map_size = np.array([10, 10, 5], dtype=np.int32)
origin = np.array([0.0, 0.0, 0.0])
obstacles = [np.array([2.0, 2.0, 1.0])]

api.configure_map(map_size, origin, 0.5, obstacles)
print("✅ Library functions working correctly!")

Virtual Environment Setup

Using uv

# Create project with uv
uv init my-drone-project
cd my-drone-project

# Add drone-pathgen dependency
uv add "git+https://github.com/u-k-g/drone-pathgen.git[viz]"

# Run your code
uv run python main.py

Next

After successful installation:

  1. Read the User Guide for basic usage

  2. Review the API Reference for detailed documentation

  3. Check out examples/ for working code