機器人學習：教程指南

摘要

機器人學習正處於一個轉折點，這是由機器學習的快速進步和大規模機器人數據的日益可用性所驅動的。從傳統的基於模型的方法轉向數據驅動、基於學習的範式，正在釋放自主系統前所未有的能力。本教程將引領讀者探索現代機器人學習的版圖，從強化學習和行為克隆的基礎原理出發，直至能夠跨多種任務甚至不同機器人形態運作的通用、語言條件模型。這項工作旨在為研究人員和實踐者提供指南，我們的目標是讓讀者具備必要的概念理解和實用工具，以貢獻於機器人學習的發展，並提供在lerobot中實現的即用示例。

English

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.

機器人學習：教程指南

Robot Learning: A Tutorial

摘要

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