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20242026
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cs.RO2026

LHM-Humanoid: Long-Horizon Human Motion Control for Continuous Object Transport in Cluttered Scenes

Haozhuo Zhang, Jingkai Sun, Michele Caprio +5

Physics-based human motion control can make a simulated character walk, sit, and manipulate objects with high physical realism. Almost always, though, this happens in short, isolat…

cs.RO2026

Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation

Yicheng Jiang, Jiaxu Wang, Junhao He +8

Current 3D-aware pretraining methods for embodied perception and manipulation are largely built on differentiable rendering frameworks, producing either fully implicit neural field…

cs.RO2026

Heracles: Bridging Precise Tracking and Generative Synthesis for General Humanoid Control

Zelin Tao, Zeran Su, Peiran Liu +13

Achieving general-purpose humanoid control requires a delicate balance between the precise execution of commanded motions and the flexible, anthropomorphic adaptability needed to r…

cs.RO2026

Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition

Jiahang Cao, Yize Huang, Hanzhong Guo +15

Diffusion-based models for robotic control, including vision-language-action (VLA) and vision-action (VA) policies, have demonstrated significant capabilities. Yet their advancemen…

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

Learning Human-Like Badminton Skills for Humanoid Robots

Yeke Chen, Shihao Dong, Xiaoyu Ji +10

Realizing versatile and human-like performance in high-demand sports like badminton remains a formidable challenge for humanoid robotics. Unlike standard locomotion or static manip…