person Tute World Team

Physical AI & Robotics Roadmap

Robots used to be creatures of science fiction. Today they drive our cars, build our products, and are beginning to walk into our homes. This roadmap takes you from absolute zero — "what even is a robot?" — all the way to building intelligent machines powered by deep learning and large foundation models. No engineering degree required.

Phase 1: Foundations

Beginner

Goal: Understand what robotics is, how robots are built, and the core mathematics needed to describe motion in space.

  • What is Robotics? History, categories, and where we're headed.
  • Robot Anatomy: Sensors, actuators, controllers, and the body.
  • Math for Robotics: Vectors, matrices, coordinate transforms, and trigonometry.
Explore Phase 1

Phase 2: Hardware & Electronics

Beginner

Goal: Get hands-on with the physical components that make robots move, sense, and think.

  • Microcontrollers & Computers: Arduino, Raspberry Pi, Jetson Nano.
  • Motors & Actuators: Servo, stepper, brushless DC motors and hydraulics.
  • Sensors: Cameras, LiDAR, ultrasonic, IMU, force sensors.
Explore Phase 2

Phase 3: Robot Software

Intermediate

Goal: Learn how to program robots — from writing your first ROS node to building full simulation environments.

  • ROS: The Robot Operating System — the lingua franca of robotics.
  • Python for Robotics: Control loops, serial comms, OpenCV, NumPy.
  • Simulation: Gazebo, NVIDIA Isaac Sim, and PyBullet.
Explore Phase 3

Phase 4: Perception & Vision

Intermediate

Goal: Give your robot eyes and a sense of where it is in the world.

  • Computer Vision: OpenCV, image processing, depth sensing.
  • Object Detection: YOLO, SSD, real-time tracking pipelines.
  • SLAM: Simultaneous Localization and Mapping — building maps in real time.
Explore Phase 4

Phase 5: Motion & Control

Intermediate

Goal: Make your robot move precisely and navigate its environment intelligently.

  • Kinematics: Forward and inverse kinematics for robotic arms.
  • Path Planning: A*, RRT, and behavior trees for navigation.
  • PID Control: The universal tool for smooth, stable movement.
Explore Phase 5

Phase 6: Physical AI

Advanced

Goal: Fuse deep learning and language models with physical robots to create truly intelligent machines.

  • Deep Learning for Robotics: CNNs, imitation learning, visual servoing.
  • RL for Robots: Training robots to walk, grasp, and navigate via reward.
  • Embodied AI: Foundation models (RT-2, Gato) that reason about the physical world.
Explore Phase 6

Phase 7: Real-World Applications

Advanced

Goal: See how everything comes together in the most exciting robotics domains on the planet.

  • Autonomous Vehicles: How self-driving cars perceive, plan, and act.
  • Industrial Robots & Cobots: Factory automation and human-robot collaboration.
  • Humanoid Robots: Boston Dynamics, Tesla Optimus, Figure — where it's all going.
Explore Phase 7

Frequently Asked Questions

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