pipeline_tag: robotics
library_name: lerobot
license: mit
Robot Learning: A Tutorial
This repository contains the source code and materials for the "Robot Learning: A Tutorial" report.
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. It aims 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.
- Paper: Robot Learning: A Tutorial
- Code/GitHub Repository: https://github.com/fracapuano/robot-learning-tutorial
- Project Page (Hugging Face Space): https://huggingface.co/spaces/lerobot/robot-learning-tutorial
Abstract
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.
Usage
For detailed usage instructions, installation guides, and various code examples, please refer to the GitHub repository. The repository provides examples covering dataset batching, data collection, real-world RL, Action Chunking with Transformers (ACT), Diffusion Policies, and optimized inference.
License
The source code examples in this repository are licensed under the MIT License. The written content of the tutorial is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.