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.
Search for a specific concept, or follow a short path from an idea to its application.
148 lessons to explore
Foundations firstFoundations / 13 min read
Behavior cloning covariate shift: when actions change the inputs
Follow behavior cloning covariate shift through a frozen policy and a two-state motion model. Compare held-out expert actions with learner-state errors, inspect visited states, and test a policy class that can represent the expert.
Foundations / 14 min read
Robot data leakage: split demonstrations by episode
Compare framewise and episodewise evaluation, then inspect downloadable train, validation, and final-test manifests with training-only preprocessing.
Foundations / 12 min read
DAgger imitation learning: label the states your policy visits
Run DAgger imitation learning one round at a time. Collect expert labels on learner rollouts, retrain on the growing dataset, and compare equal label budgets.
Foundations / 17 min read
Robot policy evaluation: success, failure, and episode counts
Evaluate robot policies with declared task rules and matched trials. Inspect a downloadable learned policy, shifted dynamics, failures, timeouts, and uncertainty.
Foundations / 12 min read
Robot learning generalization: what is actually unseen?
Map the conditions a robot policy saw during training. Compare familiar-value recombinations, unseen axis values, and extrapolation with two fitted policies and an explicit condition grid.
Foundations / 13 min read
Imitation learning: compare methods by data and expert access
Compare imitation-learning methods by their data, learned quantities, and need for expert or environment access. Locate behavior cloning, DAgger, inverse RL, and GAIL.
Foundations / 12 min read
Domain randomization: break a training shortcut
Train two policies with the same labels and example count, then randomize one nuisance feature. Inspect the learned coefficients and compare frozen familiar and shifted tests to see what domain randomization changes.
Foundations / 12 min read
Open-loop vs closed-loop simulation: what replay can test
Run the same robot policy on recorded observations and in an interactive simulation. Compare proposed actions, executed motion, and the claims each test supports.
Foundations / 12 min read
Robot foundation models: what transfers across robots?
Examine what robot foundation models transfer across tasks, scenes, and robot bodies. Compare dated RT-X, Octo, and OpenVLA papers, then calculate how evaluation weights change a ranking.
Foundations / 12 min read
Behavior cloning from observation: infer missing actions
Learn an inverse model from the learner’s own actions, infer missing expert labels, and test a cloned policy. See how poor exploration and sensing errors change the result.
Foundations / 13 min read
World models for robotics: learn dynamics, then plan
Fit a small action-conditioned world model, use it to choose a plan, and check what actually happens. See how perfect training predictions can hide a poor decision.
Foundations / 14 min read
Robotics simulation: choose the model for the question
Choose robotics simulation models by the question they can answer. Separate kinematics, force dynamics, numerical error, sensing, and hardware validation with a worked cart example.