Robotics: Science and Systems XXII

X-Loco: Towards Generalist Humanoid Locomotion Control via Synergetic Policy Distillation

Dewei Wang, Xinmiao Wang, Chenyun Zhang, Jiyuan Shi, Yingnan Zhao, Chenjia Bai, Xuelong Li

Abstract:

While recent advances have demonstrated strong performance in individual humanoid skills such as upright locomotion, fall recovery and whole-body coordination, learning a single policy that masters all these skills remains challenging due to the diverse dynamics and conflicting control objectives involved. To address this, we introduce X-Loco, a framework for training a vision-based generalist humanoid locomotion policy. X-Loco trains multiple oracle specialist policies and adopts a synergetic policy distillation with a case-adaptive specialist selection mechanism, which dynamically leverages multiple specialist policies to guide a vision-based student policy. This design enables the student to acquire a broad spectrum of locomotion skills, ranging from fall recovery to terrain traversal and whole-body coordination skills. To the best of our knowledge, X-Loco is the first framework to demonstrate vision-based humanoid locomotion that jointly integrates upright locomotion, whole-body coordination and fall recovery, while operating solely under velocity commands without relying on reference motions. Experimental results show that X-Loco achieves superior performance, demonstrated by tasks such as fall recovery and terrain traversal. Ablation studies further highlight that our framework effectively leverages specialist expertise and enhances learning efficiency.

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Bibtex:

  
@INPROCEEDINGS{WangD-RSS-26, 
    AUTHOR    = {Dewei Wang AND Xinmiao Wang AND Chenyun Zhang AND Jiyuan Shi AND Yingnan Zhao AND Chenjia Bai AND Xuelong Li}, 
    TITLE     = {{X-Loco: Towards Generalist Humanoid Locomotion Control via Synergetic Policy Distillation}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2026}, 
    ADDRESS   = {Sydney, Australia}, 
    MONTH     = {July}, 
    DOI       = {10.15607/RSS.2026.XXII.022} 
}