NavArena: 3Dガウススプラッティング再構成からの目標指向ナビゲーションベンチマークの自動構築
NavArena: Automated Construction of Goal-Oriented Navigation Benchmarks from 3D Gaussian Splatting Reconstructions
固定された3DGS再構成を、到達可能性や衝突判定、意味的目標を備えたナビゲーションベンチマークへ自動変換するフレームワークを提案し、2,000以上のシーンで2,220万の専門家軌道を生成して評価する。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
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6. 次に読むべき論文は?
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著者: Junhui Wang, Wei Yang, Xinyao Li, Ningjing Fan, Yuehao Yin, Xuecheng Chen, Chao Gao
分類: cs.RO
原文アブストラクト
Fixed 3D Gaussian Splatting (3DGS) reconstructions provide realistic novel views but lack the traversability constraints, valid goals, and closed-loop protocols required for navigation evaluation. We introduce NavArena, an automated framework that transforms fixed 3DGS reconstructions into benchmarks for goal-oriented visual navigation. NavArena integrates a frozen 3DGS model for egocentric RGB-D rendering, an occupancy costmap derived from Gaussian density and height statistics for reachability and collision queries, and semantic goal candidates lifted from multi-view open-vocabulary masks. These components support the automatic generation and unified closed-loop evaluation of goal-oriented navigation episodes. Across more than 2{,}000 scenes, NavArena generates 22.2 million expert trajectories. Spatial and semantic evaluations assess the derived navigation representations, while policy rollouts demonstrate the diagnostic value of the unified evaluation protocol. NavArena enables scalable and reproducible navigation evaluation on large-scale 3DGS reconstructions, and all benchmark-generation tools, evaluation protocols, and derived assets will be released publicly.