A Survey of Behavior Foundation Model: Next-Generation Whole-Body Control System of Humanoid Robots

TL;DR

This survey reviews the development and application of behavior foundation models for humanoid robot whole-body control, highlighting their potential for scalable, adaptable, and general-purpose robotic intelligence.

Contribution

It provides a comprehensive overview of BFM development, discusses real-world applications and limitations, and offers a curated collection of related research resources.

Findings

BFMs enable zero-shot adaptation to various tasks

Pre-training with large-scale data improves control versatility

Current limitations include real-world deployment challenges

Abstract

Humanoid robots are drawing significant attention as versatile platforms for complex motor control, human-robot interaction, and general-purpose physical intelligence. However, achieving efficient whole-body control (WBC) in humanoids remains a fundamental challenge due to sophisticated dynamics, underactuation, and diverse task requirements. While learning-based controllers have shown promise for complex tasks, their reliance on labor-intensive and costly retraining for new scenarios limits real-world applicability. To address these limitations, behavior(al) foundation models (BFMs) have emerged as a new paradigm that leverages large-scale pre-training to learn reusable primitive skills and broad behavioral priors, enabling zero-shot or rapid adaptation to a wide range of downstream tasks. In this paper, we present a comprehensive overview of BFMs for humanoid WBC, tracing their development across diverse pre-training pipelines. Furthermore, we discuss real-world applications, current limitations, urgent challenges, and future opportunities, positioning BFMs as a key approach toward scalable and general-purpose humanoid intelligence. Finally, we provide a curated and regularly updated collection of BFM papers and projects to facilitate more subsequent research, which is available at https://github.com/yuanmingqi/awesome-bfm-papers.