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Scaling generalist robotic policies is limited by the high cost of collecting embodied interaction data. Large-scale egocentric human videos offer a rich alternative, but they lack robot action labels, and existing action annotation methods are often noisy under real-world visual complexity and diverse manipulation dyn...
Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents offer a promising basis for this task, but selecting plausible local actions does not ensure that execution remains consistent with the intended route, particularly in...
A dual-layer semantic-spatial belief mapping framework that transforms transient VLM observations into persistent spatial guidance is proposed, and object-conditioned visual reasoning with conservative evidence qualification is introduced to improve observation reliability before spatial accumulation.
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