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Setup Guide

Overview​

This guide will help you set up your development environment for the Physical AI & Humanoid Robotics course. The setup process varies depending on your hardware and cloud access, but we've designed the course to be accessible with different configurations.

Prerequisites​

Basic Requirements​

  • Operating System: Linux (Ubuntu 20.04/22.04 recommended), Windows 10/11, or macOS
  • RAM: 8GB minimum, 16GB+ recommended
  • Storage: 50GB+ free space
  • Internet: Broadband connection for initial setup

Software Requirements​

  • Git: Version control system
  • Python: 3.10 or higher
  • Node.js: 18 or higher (for Docusaurus documentation)
  • Docker: Optional, for containerized environments

Installation Steps​

1. Clone the Repository​

git clone https://github.com/your-org/physical-ai-and-humanoid-robotics.git
cd physical-ai-and-humanoid-robotics

2. Install Python Dependencies​

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

3. Install Node.js Dependencies (for Docusaurus)​

cd docusaurus
npm install
cd ..

4. Verify Installation​

# Check Python environment
python -c "import numpy, pandas, torch; print('Python environment OK')"

# Check Jupyter
jupyter --version

Hardware-Specific Setup​

NVIDIA RTX Workstation Setup​

If you have an NVIDIA RTX GPU, you can take advantage of CUDA acceleration:

# Install PyTorch with CUDA support
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Verify CUDA
python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"

Jetson Platform Setup​

For NVIDIA Jetson platforms, use the appropriate PyTorch installation:

# Jetson-specific PyTorch installation
pip install torch torchvision torchaudio --index-url https://nvidia.github.io/TensorRT/tl-build/torch-tensorrt/notebooks/pytorch_install.sh

Cloud Setup Options​

Google Colab​

For cloud-based access without local hardware requirements:

  1. Upload the notebook files to Google Drive
  2. Open with Google Colab
  3. Install required packages in the notebook:
!pip install -r requirements.txt

AWS/GCP/Azure Instances​

For dedicated cloud instances:

  1. Launch GPU instance (recommended: p3, p4, or G2 instances)
  2. Follow the standard installation steps above
  3. Set up Jupyter notebook server with proper security settings

Jupyter Notebook Setup​

Starting Jupyter​

# From the project root
jupyter notebook

Notebook Execution Tips​

  • Always run notebooks from the project root directory
  • Use the provided virtual environment
  • For notebooks requiring hardware, check for --simulation flags

Docusaurus Documentation Setup​

Local Development Server​

cd docusaurus
npm start

This will start a local development server at http://localhost:3000.

Building Documentation​

cd docusaurus
npm run build

Testing Your Setup​

Run Basic Tests​

# Python tests
python -c "import numpy, pandas, matplotlib, seaborn; print('Basic Python packages OK')"

# FastAPI demo
cd demo
python -c "import fastapi; print('FastAPI OK')"
cd ..

Execute Sample Notebook​

cd notebooks
jupyter nbconvert --to notebook --execute chapter-01-ros2.ipynb --ExecutePreprocessor.timeout=600

Troubleshooting​

Common Issues​

Python Package Installation​

If you encounter issues with package installation:

# Upgrade pip first
python -m pip install --upgrade pip

# Install packages individually if needed
pip install numpy pandas matplotlib

Node.js Issues​

If Docusaurus installation fails:

# Clear npm cache
npm cache clean --force

# Reinstall dependencies
rm -rf node_modules package-lock.json
npm install

CUDA Issues​

For CUDA-related problems:

# Check CUDA version
nvidia-smi

# Install appropriate PyTorch version
# Visit pytorch.org for the correct command for your CUDA version

Performance Considerations​

  • For notebooks with 3D simulation, ensure adequate GPU memory
  • Use --simulation mode if running on CPU-only systems
  • Consider using smaller model variants for initial testing

Optional Configurations​

IDE Setup​

VS Code​

  • Install Python extension
  • Install Jupyter extension
  • Configure to use project virtual environment

PyCharm​

  • Configure interpreter to use virtual environment
  • Enable Jupyter integration

Environment Variables​

Create a .env file in the project root:

OPENAI_API_KEY=your_key_here
CUDA_VISIBLE_DEVICES=0

Verification Checklist​

Before proceeding with the course, verify:

  • Python virtual environment activated
  • Jupyter notebook accessible
  • Docusaurus documentation builds
  • Basic Python packages import successfully
  • Sample notebook executes (even in simulation mode)
  • Git repository properly cloned

Next Steps​

Once your setup is complete, proceed to:

  1. Read the Course Introduction
  2. Review the 13-Week Schedule
  3. Begin with Module 1: ROS 2

Support​

If you encounter setup issues not covered here:

  • Check the GitHub issues page
  • Join our Discord community
  • Contact the course staff during office hours