About Robotics Engineering
Robotics engineering is the craft of building machines that sense, decide, and act in
the physical world, and this course walks through it in the order most engineers
actually learn it. It starts with Math & Physics Foundations
(linear algebra, coordinate frames, and mechanics), then
Programming for Robotics and
Electronics & Embedded Systems so you can write code and wire
real hardware.
Next comes Sensors & Actuators: motors, encoders, IMUs, cameras,
and lidar, and how to read and drive them reliably. From there,
Control Systems covers PID, feedback, and state-space methods, while
Kinematics & Dynamics covers forward and inverse kinematics,
Jacobians, and how forces move a robot.
ROS 2 & Robot Software covers nodes, topics, transforms, and
launch files, and Perception & Computer Vision covers OpenCV,
point clouds, sensor fusion, and SLAM.
Finally, Motion Planning & Navigation covers path search,
sampling-based planners, and manipulation planning, and
Machine Learning & Simulation covers Gazebo, reinforcement
learning, and safe deployment: the skills that separate a robot that works on the
bench from one that works in the real world.
Content
10 modules
01
Math & Physics Foundations
Linear algebra, probability, coordinate frames, and the classical mechanics that every robot model builds on.
Linear AlgebraTransformationsMechanics
02
Programming for Robotics
Writing clean, real-time-friendly code: Python for fast prototyping and C++ for performance-critical robot software.
PythonC++Linux & Git
03
Electronics & Embedded Systems
Circuits, power, and microcontrollers, plus the communication protocols that connect a robot's parts.
ArduinoSTM32 / ESP32I2C / SPI / UART
04
Sensors & Actuators
Reading the world with encoders, IMUs, cameras, and lidar, and moving through it with DC, stepper, and servo motors.
IMULidarMotor Drivers
05
Control Systems
Feedback control from PID tuning to state-space design, and how to keep a robot stable and responsive.
PIDState-SpaceKalman Filter
06
Kinematics & Dynamics
Modelling how robot arms and mobile bases move: forward and inverse kinematics, Jacobians, and equations of motion.
Forward / Inverse KinematicsJacobiansURDF
07
ROS 2 & Robot Software
Structuring robot software with nodes, topics, services, and actions, and managing frames with tf2.
ROS 2tf2Launch Files
08
Perception & Computer Vision
Turning raw sensor data into understanding: image processing, object detection, point clouds, and SLAM.
OpenCVPoint CloudsSLAM
09
Motion Planning & Navigation
Finding safe, efficient paths with graph search and sampling-based planners, for mobile robots and manipulators alike.
A*RRTNav2 / MoveIt
10
Machine Learning & Simulation
Testing in simulation, learning behaviours with reinforcement and imitation learning, and deploying safely on real hardware.
GazeboReinforcement LearningSim-to-Real
What You Can Do After This Course
By the end of the curriculum you'll have worked through 5 hands-on projects and
covered the core of what a junior to mid-level robotics role expects. Concretely,
you'll be able to:
Model a robot mathematically: use coordinate frames, transformations, and kinematic chains to describe how a robot moves.
Write robot code: build in Python and C++, tracked with Git and running on Linux and microcontrollers.
Wire and drive hardware: connect sensors, motors, and microcontrollers into a working electromechanical system.
Control motion: tune PID loops and apply state estimation so your robot behaves predictably.
Build with ROS 2: structure a robot's software into nodes, topics, and services that you can test and reuse.
Perceive and navigate: process camera and lidar data, build maps with SLAM, and plan collision-free paths.
Simulate, learn, and deploy: validate in Gazebo, apply machine learning where it helps, and move to real hardware with safety in mind.