Robot Learning: A Tutorial
Authors: name: Francesco Capuano, name: Caroline Pascal, name: Adil Zouitine, name: Thomas Wolf, name: Michel Aractingi
Organization: LeRobot

Robot learning is at an inflection point, driven by rapid advancements in
machine learning and the growing availability of large-scale robotics data.
This shift from classical, model-based methods to data-driven, learning-based
paradigms is unlocking unprecedented capabilities in autonomous systems. This
tutorial navigates the landscape of modern robot learning, charting a course
from the foundational principles of Reinforcement Learning and Behavioral
Cloning to generalist, language-conditioned models capable of operating across
diverse tasks and even robot embodiments. This work is intended as a guide for
researchers and practitioners, and our goal is to equip the reader with the
conceptual understanding and practical tools necessary to contribute to
developments in robot learning, with ready-to-use examples implemented in
lerobot.