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20242026
most citedTri-Modal Motion Retrieval by Learning a Joint Embedding Space

2 citations · 2 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.RO2026

SOLO: Stable Omni-terrain Long-Horizon Perceptive Humanoid Locomotion

Pihai Sun, Gang Han, Jingkai Sun +17

Humans traverse complex terrain over long distances without losing balance, whereas perceptive humanoid policies become fragile as perception and control errors accumulate. We pres…

cs.RO2026

Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking

Tao Huang, Ruofei Liu, Xuchen Tang +15

Humanoid robots have recently demonstrated promising capabilities in real-world ball sports. However, achieving professional motion styles while maintaining strong task performance…

cs.RO2026

RoboStriker: Latent-Space Strategic Games for Autonomous Humanoid Boxing

Kangning Yin, Kaige Liu, Zhe Cao +9

Achieving human-level competitive intelligence and physical agility in humanoid robots remains a profound challenge, particularly in contact-rich and highly dynamic tasks such as b…

cs.RO2026

Scaling Behavior Foundation Model for Humanoid Robots

Weishuai Zeng, Kangning Yin, Xiaojie Niu +15

Humanoid control requires natural whole-body coordination, precise real-time responses to control signals, and robust generalization across diverse environmental contexts, making i…

cs.RO2026

MeshMimic: Geometry-Aware Humanoid Motion Learning through 3D Scene Reconstruction

Qiang Zhang, Jiahao Ma, Peiran Liu +20

Humanoid motion control has witnessed significant breakthroughs in recent years, with deep reinforcement learning (RL) emerging as a primary catalyst for achieving complex, human-l…

cs.RO2026

RoboStriker: Hierarchical Decision-Making for Autonomous Humanoid Boxing

Kangning Yin, Zhe Cao, Wentao Dong +7

Achieving human-level competitive intelligence and physical agility in humanoid robots remains a major challenge, particularly in contact-rich and highly dynamic tasks such as boxi…

cs.RO2025

Unveiling the Impact of Data and Model Scaling on High-Level Control for Humanoid Robots

Yuxi Wei, Zirui Wang, Kangning Yin +3

Data scaling has long remained a critical bottleneck in robot learning. For humanoid robots, human videos and motion data are abundant and widely available, offering a free and lar…

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

Behavior Foundation Model for Humanoid Robots

Weishuai Zeng, Shunlin Lu, Kangning Yin +4

Whole-body control (WBC) of humanoid robots has witnessed remarkable progress in skill versatility, enabling a wide range of applications such as locomotion, teleoperation, and mot…

cs.RO2025

UniTracker: Learning Universal Whole-Body Motion Tracker for Humanoid Robots

Kangning Yin, Weishuai Zeng, Ke Fan +7

Achieving expressive and generalizable whole-body motion control is essential for deploying humanoid robots in real-world environments. In this work, we propose UniTracker, a three…