1回のスキャンで十分：言語誘導ナビゲーションのためのデモンストレーション不要な適応
One Scan is Enough: Demonstration-Free Adaptation for Language-Guided Navigation
iPhoneでの短時間スキャンから訓練環境と指示付きナビゲーションエピソードを自動生成し、人間のデモなしで言語誘導ナビゲーション方策を新しい建物に適応させる手法を提案した。
著者: Zhuoyuan Yu, Yuxing Long, Du Wang, Junyang Wang, Hongwei Fan, Hao Dong
分類: cs.RO, cs.AI, cs.CL, cs.CV, cs.LG
原文アブストラクト
Deploying a language-guided navigation policy in a new building usually means watching it fail. Public-benchmark VLAs degrade scene by scene as layout, appearance, and language drift, and the standard fix of teleoperating fresh trajectories on site does not scale. We replace human demonstration with a single brief iPhone scan. Scan2Instruction compiles that scan into a complete training environment, automatically synthesizing executable navigation episodes with grounded instructions. PRPT-KS then adapts the policy through a closed-form Pareto utility read directly off the reconstructed scene, with no learned critic and no human labels. Across five real environments, the two designs together drive our RealNav to an 85% real-robot success rate, compared with 49% for a RealNav baseline post-trained on human demonstrations, and still achieve 82% in unscanned regions of the same buildings, compared with 41% for the same baseline. Our work turns demonstration-free scene adaptation for language-guided navigation from an aspiration into a working reality.