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cs.RO2026

Scaling Behavior Foundation Model for Humanoid Robots

Weishuai Zeng, Kangning Yin, Xiaojie Niu +15

The paper proposes a scalable behavior foundation model for humanoid robots that uses a motion‑tracking learning paradigm, coordinated on‑policy rollouts and diverse reference moti…

cs.RO2026

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

Xiao Chen, Weishuai Zeng, Xiaojie Niu +12

While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a result, they are vulnerable to en…

cs.RO2026

Imagine2Real: Towards Zero-shot Humanoid-Object Interaction via Video Generative Priors

Jiahe Chen, ZiRui Wang, Feiyu Jia +7

Whole-body Humanoid-Object Interaction (HOI) is bottlenecked by the scarcity of high-fidelity 3D data. While video generative priors offer a promising alternative, existing methods…

cs.RO2025

Towards Adaptable Humanoid Control via Adaptive Motion Tracking

Tao Huang, Huayi Wang, Junli Ren +8

Humanoid robots are envisioned to adapt demonstrated motions to diverse real-world conditions while accurately preserving motion patterns. Existing motion prior approaches enable w…

cs.RO2025

PhysHSI: Towards a Real-World Generalizable and Natural Humanoid-Scene Interaction System

Huayi Wang, Wentao Zhang, Runyi Yu +10

Deploying humanoid robots to interact with real-world environments--such as carrying objects or sitting on chairs--requires generalizable, lifelike motions and robust scene percept…

cs.RO2025

Learning Humanoid Standing-up Control across Diverse Postures

Tao Huang, Junli Ren, Huayi Wang +6

Standing-up control is crucial for humanoid robots, with the potential for integration into current locomotion and loco-manipulation systems, such as fall recovery. Existing approa…