ProtoVis-Nav: 視覚空間整合型UAVナビゲーションのためのプロトタイプ視覚想像
ProtoVis-Nav: Prototypical Visual Imagination for Visual-Spatial Aligned UAV Navigation
UAVの視覚言語ナビゲーションにおいて、次の移動先の局所視覚表現をプロトタイプの線形結合で想像してから経路点を生成することで、言語指示と3D動作の整合性を高める手法を提案した。
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著者: Guangyuan Sui, Yunzhong Hou, Chi Harold Liu
分類: cs.RO, cs.CV
原文アブストラクト
Vision language navigation (VLN) is very challenging for Unmanned Aerial Vehicles (UAVs) since small errors in 3D motion prediction can lead to navigation errors and collisions. Unable to fathom execution outcomes in 3D environments, existing methods often struggle to predict accurate navigation waypoints from language instructions. To solve this, we introduce the Prototypical Visual Imagination framework, shortened as ProtoVis-Nav, which forces the model to imagine an outcome-associated local visual representation for the intended next UAV movement. Specifically, we predict feature prototypes and use their linear combination to estimate the visual feature of the target region. In this manner, the VLN model first imagines the local visual representation of the next intended location, and then uses predicted prototypes as context for generating the final action, promoting alignment between visual context and waypoint outputs. Extensive experiments demonstrate the effectiveness of the ProtoVis-Nav framework and show substantial improvements over existing baselines.