境界を越える視覚：人間とロボットの相互作用におけるドメイン特化型大規模視覚モデルの初期設計空間
Vision Beyond Boundaries: An Initial Design Space of Domain-specific Large Vision Models in Human-robot Interaction
人間とロボットの相互作用（HRI）にドメイン特化型の大規模視覚モデルを適用するための設計空間を提案し、15名の専門家による評価で有効性を示した。
著者: Yuchong Zhang, Yong Ma, Danica Kragic
分類: cs.HC, cs.RO
原文アブストラクト
The emergence of large vision models (LVMs) is following in the footsteps of the recent prosperity of Large Language Models (LLMs) in following years. However, there's a noticeable gap in structured research applying LVMs to human-robot interaction (HRI), despite extensive evidence supporting the efficacy of vision models in enhancing interactions between humans and robots. Recognizing the vast and anticipated potential, we introduce an initial design space that incorporates domain-specific LVMs, chosen for their superior performance over normal models. We delve into three primary dimensions: HRI contexts, vision-based tasks, and specific domains. The empirical evaluation was implemented among 15 experts across six evaluated metrics, showcasing the primary efficacy in relevant decision-making scenarios. We explore the process of ideation and potential application scenarios, envisioning this design space as a foundational guideline for future HRI system design, emphasizing accurate domain alignment and model selection.
