一緒に歩こう：人間中心の屋外支援のための長期的社会的ナビゲーション
Walk With Me: Long-Horizon Social Navigation for Human-Centric Outdoor Assistance
高レベルの自然言語指示から屋外での長期的な社会的ナビゲーションを実現する、地図不要のフレームワークを提案。GPSと公開地図APIのPOIを用いて目的地を推定し、高レベルVLMと低レベルVLAを状況に応じて切り替えることで、安全で社会的に適切な移動を実現する。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Lingfeng Zhang, Xiaoshuai Hao, Xizhou Bu, Yingbo Tang, Hongsheng Li, Jinghui Lu, Xiu-shen Wei, Jiayi Ma, Yu Liu, Jing Zhang, Hangjun Ye, Xiaojun Liang, Long Chen, Wenbo Ding
分類: cs.RO
原文アブストラクト
Assisting humans in open-world outdoor environments requires robots to translate high-level natural-language intentions into safe, long-horizon, and socially compliant navigation behavior. Existing map-based methods rely on costly pre-built HD maps, while learning-based policies are mostly limited to indoor and short-horizon settings. To bridge this gap, we propose Walk with Me, a map-free framework for long-horizon social navigation from high-level human instructions. Walk with Me leverages GPS context and lightweight candidate points-of-interest from a public map API for semantic destination grounding and waypoint proposal. A High-Level Vision-Language Model grounds abstract instructions into concrete destinations and plans coarse waypoint sequences. During execution, an observation-aware routing mechanism determines whether the Low-Level Vision-Language-Action policy can handle the current situation or whether explicit safety reasoning from the High-Level VLM is needed. Routine segments are executed by the Low-Level VLA, while complex situations such as crowded crossings trigger high-level reasoning and stop-and-wait behavior when unsafe. By combining semantic intent grounding, map-free long-horizon planning, safety-aware reasoning, and low-level action generation, Walk with Me enables practical outdoor social navigation for human-centric assistance.
