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Native Video-Action Pretraining for Generalizable Robot Control
Qihang Zhang, Lin Li, Luyao Zhang +26
The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed for digital content creation i…
A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulation
Yi-Xiang He, Lan Wei, Haoming Cen +6
Multi-robot systems provide the parallelism and redundancy necessary for long-horizon tasks, while Large Language Models (LLMs) offer the reasoning capabilities to decompose these…
BrickCraft: Visuomotor Skill Composition with Situated Manual Guidance for Long-Horizon Interlocking Brick Assembly
Jichuan Yu, Bowei Li, Zhenran Tang +4
Autonomous robotic assembly of interlocking bricks demands seamless integration of long-horizon task reasoning, spatial grounding, and fine-grained manipulation. This paper present…
Human-in-the-loop Online Rejection Sampling for Robotic Manipulation
Guanxing Lu, Rui Zhao, Haitao Lin +2
Reinforcement learning (RL) is widely used to produce robust robotic manipulation policies, but fine-tuning vision-language-action (VLA) models with RL can be unstable due to inacc…
RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation
Yuquan Xue, Guanxing Lu, Zhenyu Wu +4
Vision-Language-Action (VLA) models have shown strong manipulation capability when trained with large-scale imitation learning datasets. However, these datasets that predominantly…
RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation
Chuanrui Zhang, Zhengxian Wu, Guanxing Lu +2
Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently lack the spatial and kinematic re…