AUTHOR=Mirza Khojasteh Z. , Singh Shubham 

TITLE=Imitation learning for legged robot locomotion: a survey

JOURNAL=Frontiers in Robotics and AI

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1678567

DOI=10.3389/frobt.2025.1678567

ISSN=2296-9144

ABSTRACT=Imitation learning (IL) has fundamentally transformed the field of legged robot locomotion, removing the dependence on hand-engineered reward functions. Since 2019, this area of research has progressed rapidly, from simple motion-capture replication to the generation of sophisticated policies using diffusion models. This survey offers a comprehensive analysis of 35 pivotal research works, using a structured six-dimensional framework to investigate advancements using quadrupedal and humanoid platforms. The review also pinpoints significant challenges related to deployment and outlines new research directions. A key finding from the survey indicates that behavior cloning is utilized in almost half of the analyzed studies. Moreover, data generated through model-predictive control (MPC) now represents the most frequently used training data source for advanced imitation learning systems.