Learning library

Understand how a robot works.

Build working knowledge of robotics and machine learning through examples you can change, calculations you can check, and data you can inspect.

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148 lessons to explore

Foundations first

  1. Foundations / 12 min read

    Bode plots and loop shaping: place gain and phase together

    Read Bode plots and shape a position-control loop with a lead controller. Calculate crossover and phase margin, compare closed-loop tracking, and check what the model leaves out.

  2. Foundations / 12 min read

    Control bandwidth: tracking speed and physical limits

    Calculate closed-loop bandwidth relative to DC gain, then compare sinusoidal tracking with the torque it requires. Separate bandwidth from loop crossover and account for resonance, delay, sampling, and noise.

  3. Foundations / 11 min read

    Controller discretization: sample, compute, and hold

    Explore controller discretization with exact held-input dynamics. Compare immediate and delayed commands, calculate discrete poles, and connect sample timing to control stability.

  4. Foundations / 13 min read

    ICP algorithm explained: align two scans step by step

    Learn how ICP aligns two point sets. Step through the lab, download the same data and Python solver, and compare a correct fit with misleading residuals.

  5. Foundations / 8 min read

    Moravec’s paradox: the hidden work of picking up a cup

    Follow one cup from perception to grasping and recovery. Learn what Moravec’s paradox means, check a grasp’s clearance, and assess a robot demonstration.

  6. Foundations / 16 min read

    Behavior cloning: learn robot actions from demonstrations

    Learn behavior cloning with an interactive robot example and downloadable Python exercise. Split episodes, fit a policy, and compare action error with rollouts.

  7. Foundations / 13 min read

    SLAM in robotics: estimate a robot’s path and its map

    Understand SLAM in robotics by solving a small landmark problem. Compare localization, mapping, and joint estimation, then see how anchoring and measurement weights change the answer.

  8. Foundations / 10 min read

    Loop closure in SLAM: why revisiting a place changes the map

    Follow a supplied loop measurement through a small SLAM graph. See how its weight changes the whole route, and why a false revisit can lower cost while increasing error.

  9. Foundations / 12 min read

    Sim-to-real transfer: train for a model that changes

    Explore sim-to-real transfer by fitting a policy across actuator models. Test unseen gains, compare goal error and effort, and distinguish simulation checks from hardware evidence.

  10. Foundations / 9 min read

    What is physical AI? Follow a robot from sensing to action

    Follow a mobile robot from sensing to action. Compare physical AI and embodied AI, locate learned and classical methods, and calculate how measurement bias changes a stop.

  11. Foundations / 10 min read

    Covariance and uncertainty ellipses: read the shape of error

    Read a covariance matrix as a geometric description of spread. Rotate an uncertainty ellipse, compare a Gaussian model with a finite sample, and calculate what a 95% contour means.

  12. Foundations / 12 min read

    Kalman filter: predict position, then correct with measurements

    Work through a scalar Kalman update, then estimate position and velocity from noisy readings. Explore missing measurements, covariance, and a biased sensor that defeats the filter’s assumptions.