A practical curriculum guide that pairs core theory with trusted resources and follow-along projects from first simulations to ROS 2, controls, sensing, and autonomy.
Each stage balances theory, implementation, and build practice so the material compounds instead of becoming a list of disconnected courses.
Build the math, programming, and physics base needed to reason about robots as moving physical systems.
Topics
Add algorithms, electronics, probability, and dynamic systems so software can meet hardware cleanly.
Topics
Study the robot-specific core: kinematics, dynamics, controls, sensors, embedded systems, and ROS 2.
Topics
Turn the core into autonomy with perception, planning, learning, safety, and an integrated capstone.
Topics
These links favor free or widely used materials that can anchor an independent study plan.
A strong base for kinematics, estimation, controls, and almost every serious robotics topic.
Book, videos, and software for rigid-body motion, kinematics, dynamics, control, and planning.
The reference point for nodes, topics, services, transforms, packages, and middleware concepts.
A hands-on introduction to building AI-enabled robots with modern software and hardware tools.
Introductory robotics lessons connected to learning-based systems and open-source tooling.
Self-paced courses for Isaac Sim, Isaac Lab, Isaac ROS, digital twins, and sim-to-real workflows.
Only the proposals with complete phases, safety constraints, parts lists, and reference links are published here.
Build a small remote-controlled car, then add telemetry and speed feedback as a robotics foundation.
Build a roughly 9-inch (230-250 mm) motor-to-motor quadcopter with 5-inch propellers, PX4 flight control, telemetry, and a logged autonomous mission.