Cognitive Action Reasoning for Proactive Robots from Human-Centered Multimodal Observations
Robots operating in human-centered environments are typically designed to execute explicit instructions, and most robot-learning datasets likewise pair observations with task instructions or low-level actions. Although recent work has begun to explore proactive embodied assistance, existing resources target different settings and action levels, leaving real-world human-centered multimodal decision-making underexplored. We formulate this problem as \textit{Proactive Robot Action Reasoning} (\textit{ProRobo}), an upstream cognitive decision problem in which a robot must determine which action to take based on multimodal human and environmental cues without explicit action instructions. To s...
| Authors | Zhihao Gu, Kechao Zhu, Yuanfeng Wu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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