Robot learning is a research field at the intersection of machine learning and robotics. It studies techniques allowing a robot to acquire novel skills or adapt to its environment through learning …

Robot learning is a collection of algorithms and methodologies that help a robot learn new skills such as manipulation, locomotion, and classification in either a simulated or real-world environment.

Oct 14, 2025 · 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 …

This web page lets you read the full Robot Learning tutorial, navigate its sections with an auto‑generated table of contents, and switch between light and dark themes. You can also download the art...

This course dives deep into robot learning, looks at fundamental algorithms and challenges, and case-studies of real-world applications from self-driving to manipulation.

Our goal is to develop intelligent robotic systems that can perceive, plan, and act in complex environments and improve performance with experience.

What is it about interacting with the world that is so hard for robots? The Robot Learning stream addresses this challenge through the lens of machine learning, in pursuit of developing generally …

Robots need to make sequential decisions to operate in the world and generalize to diverse environments. How can they learn to do so? This is what we call the "robot learning" problem, and it …

Robot learning consists of a multitude of machine learning approaches, particularly reinforcement learning, inverse reinforcement learning and regression methods.

About UC Berkeley's Robot Learning Lab, directed by Professor Pieter Abbeel, is a center for research in robotics and machine learning.