Robotics
A unified curriculum covering mathematical foundations, kinematics, sensing & perception, state estimation, control systems, path planning, and decentralized swarm coordination. 46 lessons, most with interactive canvas simulations, the rest deep-dive readings.
Foundations & Kinematics
Sensing & Perception
Control Systems
- #05 Feedback Control How a machine argues with reality, and wins, a thousand times a second
- #5.1 PID Control Three terms that run almost every machine you've ever touched
- #5.2 Transfer Functions One recipe card for every input a system will ever see
- #5.3 Poles & Zeros Two dots on a plane that decide whether your robot settles, sings, or self-destructs
- #5.4 Bode Plots Two semi-log graphs that show how a system answers slow questions versus fast ones
- #5.5 Nyquist Stability One squiggle in the complex plane decides whether your loop holds or screams
- #5.6 Root Locus A map of every place your poles can run as you crank the gain
- #5.7 State-Space Stop chasing one output at a time. Describe the whole machine as a single vector that knows where it's going next
- #5.8 Controllability & Observability Two yes/no questions that decide whether a robot can be driven, and whether it can be known
- #5.9 Observers Seeing the states you were never allowed to measure
- #5.91 Capstone: Motor Speed Control Close a PID loop around a real spinning thing and refuse to let the load win
- #5.92 Capstone: Inverted Pendulum The falling broomstick that every control engineer learns to catch
- #5.93 Capstone: Quadrotor Altitude Four spinning blades, one number to hold, and gravity pulling the whole time
State Estimation & Filters
- #06 The Robot's Dilemma Why a moving robot is always a little bit lost
- #07 Complementary Filter Two sensors that lie in opposite directions, and the one line of code that makes them tell the truth
- #08 Kalman Filter The math that flew Apollo to the Moon
- #09 Particle Filter How a thousand wrong guesses find the truth
Simultaneous Localization & Mapping
Path & Motion Planning
Introduction to Swarm Robotics
Swarm Behaviors & Formations
- #17 Boids Flocking Three rules, no leader, one mind
- #18 Potential Fields Let the landscape do the steering
- #19 Escaping Local Minima How a perfectly rational robot walks into a dead end and refuses to leave
- #20 READ Distance-Based Formations How a swarm holds its shape with no leader and no map
- #21 Cyclic Pursuit How a leaderless team surrounds a target with only local sensing
Distributed Consensus & Task Allocation
- #22 Average Consensus How a crowd agrees on a number with nobody in charge
- #23 READ Laplacian Flow How agreement spreads like heat through a network
- #24 READ Gossip Consensus How a swarm agrees on the truth without ever holding a meeting
- #25 Rendezvous How a leaderless swarm agrees on a place to meet
- #26 READ Why Greedy Fails Why grabbing the nearest job wrecks the whole team
- #27 READ Auction Algorithm How robots divide the work by bidding against each other
- #28 READ Exploration vs Exploitation The slot-machine math that tells a swarm when to gamble
- #29 READ When Robots Lie Reaching agreement when some of the voters are adversaries
Spatial Coverage & Exploration
- #30 Voronoi Coverage How a swarm divides the world into fair shares with Lloyd's algorithm
- #31 READ Frontier Exploration Always drive toward the edge of what you don't know
- #32 Pheromones & Stigmergy How a colony solves problems no single ant could
- #33 Swarm Sandbox Three good ideas, fighting for the wheel