Full-Stack + AI

Physical AI & Humanoid Robotics Textbook

Panaversity Hackathon I submission: a production-grade AI-native textbook platform teaching Physical AI and Humanoid Robotics across 13 weeks. Covers ROS 2, Gazebo, NVIDIA Isaac Sim, and a Conversational Humanoid capstone. Backend deployed on Hugging Face Spaces; FastAPI + SQLAlchemy + Qdrant Cloud with BAAI/bge-small-en-v1.5 FastEmbed for RAG; Groq LLaMA 3.3 70B for answers.

// Problem

Online robotics courses assume identical hardware for every learner and offer no help when students get stuck mid-lesson. This platform adapts content to each student’s hardware setup and answers questions in real time — deployed on live cloud infrastructure.

// Solution

A full-stack AI-native textbook platform with four progressive modules: (1) ROS 2 — nodes, topics, services, URDF, Python-ROS controllers; (2) Gazebo & Unity — physics simulation with LiDAR, depth cameras, IMUs; (3) NVIDIA Isaac — photorealistic sim, Isaac ROS, hardware-accelerated VSLAM, Nav2 path planning, sim-to-real RL; (4) Conversational Humanoid capstone — LLM-powered natural language robot interaction. Platform features: RAG chatbot (Qdrant + FastEmbed BAAI/bge-small-en-v1.5 + Groq), hardware-aware personalization at signup across 3 rig profiles, one-click Roman Urdu chapter translation, JWT auth with 3-step hardware onboarding, admin dashboard with Qdrant reindexing.

// Screenshots

RAG chatbot in action — highlight any text, click Ask AI, get an instant contextual answer from Groq LLaMA 3.3 70B

3-step hardware onboarding — Account → Skill Level → Hardware rig selection at signup

Hardware Dashboard — personalized learning path configured per rig: Sim Rig, Jetson, or Unitree G1

Live ROS 2 chapter — Python Node implementation with rclpy, actual code running on the platform

13-week curriculum roadmap with per-user progress tracking — 2/13 weeks completed, saves to PostgreSQL

Chapter page with hardware-aware content — Sim Rig label active, Ask AI button inline with the text

Full backend API — Authentication, Student Profile, Chat, Admin, Personalization, Translations, Curriculum endpoints

// Tech Stack

[Docusaurus v3][React 19][TypeScript][Tailwind CSS][FastAPI][Python 3.12][FastEmbed (BAAI/bge-small-en-v1.5)][Qdrant Cloud][Groq LLaMA 3.3 70B][SQLAlchemy][Alembic][PyJWT][GitHub Actions][GitHub Pages][Docker][Hugging Face Spaces]

// Metrics

✓13-week curriculum across 4 modules (ROS 2 → Gazebo → Isaac → Conversational Humanoid)
✓Qdrant Cloud collection 'physical-ai-docusaurus-textbook' — BAAI/bge-small-en-v1.5 384-dim vectors
✓9 SQLAlchemy models: User, StudentProfile, HardwareConfig, CurriculumProgress, ChatSession, ChatMessage, CurriculumWeek, IngestionLog, ReindexJob
✓3 hardware profiles with fully personalized content paths (RTX Sim Rig, Jetson Edge Kit, Unitree G1)
✓All hackathon bonus deliverables completed: Auth + Personalization + Urdu Translation

// Highlights

→RAG pipeline: FastEmbed (BAAI/bge-small-en-v1.5) embeds queries → Qdrant cosine search → Groq LLaMA 3.3 70B generates answer — highlight any text → Ask AI
→GrokClient auto-detects provider from API key prefix: gsk_ routes to Groq, xai- routes to xAI Grok — same code, zero config change
→Hardware-aware onboarding at signup: content adapts to RTX workstation, Jetson edge kit, or Unitree G1
→One-click Roman Urdu translation for every chapter — translations API endpoint backed by Groq
→Admin dashboard with curriculum ingestion pipeline and Qdrant reindexing endpoint
→Full CI/CD: GitHub Actions auto-deploys Docusaurus to GitHub Pages; backend on HF Spaces

Live Demo GitHub