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cs.RO2026

RoboReact: Agentic Skill Distillation from Generated Egocentric Videos for Generalizable Whole-Body Manipulation

Shuliang He, Shuai Wang, Bo Yue +3

Humanoid robots have the potential to perform dexterous manipulation in human environments, yet acquiring diverse and generalizable skills remains costly due to expensive hardware…

cs.RO2026

Grounding Sim-to-Real Generalization in Robotic Manipulation: An Empirical Study with Vision-Language-Action Models

Ruixing Jin, Zicheng Zhu, Ruixiang Ouyang +4

Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data collection, a practical alternative i…

cs.RO2026

From Reaction to Anticipation: Proactive Failure Recovery through Agentic Task Graph for Robotic Manipulation

Sheng Xu, Ruixing Jin, Huayi Zhou +6

Although robotic manipulation has made significant progress, reliable execution remains challenging because task failures are inevitable in dynamic and unstructured environments. T…

cs.RO2025

Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recovery

Bo Yue, Sheng Xu, Kui Jia +1

Humanoid robots represent a central frontier in embodied intelligence, as their anthropomorphic form enables natural deployment in humans' workspace. Brain-body co-design for human…

cs.RO2025

Embracing Evolution: A Call for Body-Control Co-Design in Embodied Humanoid Robot

Guiliang Liu, Bo Yue, Yi Jin Kim +1

Humanoid robots, as general-purpose physical agents, must integrate both intelligent control and adaptive morphology to operate effectively in diverse real-world environments. Whil…

cs.RO2025

Real-Time Verification of Embodied Reasoning for Generative Skill Acquisition

Bo Yue, Shuqi Guo, Kaiyu Hu +4

Generative skill acquisition enables embodied agents to actively learn a scalable and evolving repertoire of control skills, crucial for the advancement of large decision models. W…