4-Week AI & Robotics Curriculum
Week 1 — Mathematics, Programming & Robotics Foundations
- Mathematics for Robotics
- Vectors and matrices
- Matrix multiplication
- Coordinate systems
- Trigonometry
- Derivatives and basic calculus
- Practice: calculate robot position from coordinate transformations.
- C++/Pyton & Robotics Coding
- C++/Python fundamentals
- Functions, classes and objects
- NumPy
- Data structures
- Basic robot-control programs
- Practice: write Python code to control a simulated robot.
Week 2 — Robot Design, Kinematics & Control
- Robotics Design & Mechanical Systems
- Robot types and architectures
- Motors, servos and actuators
- Sensors
- End effectors
- CAD/design principles
- Power and electronics basics
- Practice: design a simple 2-wheel mobile robot or robotic arm.
- Kinematics, Dynamics & Motion
- Forward kinematics
- Inverse kinematics
- Coordinate frames
- Rotation matrices
- Homogeneous transformations
- Velocity and acceleration
- Practice: calculate the position of a 2- or 3-joint robotic arm.
Week 3 — Computer Vision & AI
- Computer Vision (CV)
- Images and pixels
- OpenCV
- Image filtering
- Edge detection
- Contours
- Object detection
- Camera calibration
- Practice: build a program that detects and tracks an object using a webcam.
- AI & Machine Learning for Robotics
- AI fundamentals
- Supervised vs. unsupervised learning
- Classification and regression
- Neural networks
- Training/testing datasets
- AI perception for robots
- Practice: train a simple model to classify objects or recognise robot environments.
Week 4 — Motion Planning & Integrated Project
- Motion Planning + Final Robotics Project
- Configuration space
- Collision detection
- Path planning
- A*
- Dijkstra's algorithm
- RRT/RRT*
- Obstacle avoidance
- Basic feedback control
- Practice: program a simulated robot to navigate from Start → Goal while avoiding obstacles.
Final 4-Week Project
Build a vision-guided autonomous robot:
Camera → Computer Vision → AI Decision → Motion Planning → Motor Control
For example:
Robot detects an object → identifies it → calculates where it is → plans a collision-free path → moves toward it → stops at the target.
Suggested Weekly Structure
- Day 1: Theory
- Day 2: Mathematics
- Day 3: Coding
- Day 4: Robotics design
- Day 5: Practical/simulation
- Day 6: Project work
- Day 7: Review + assessment
Recommended tools: Python, NumPy, OpenCV, Ma