身体性ナビゲーションにおける知覚・社会・運動知能:包括的サーベイ
Sensing, Social, and Motion Intelligence in Embodied Navigation: A Comprehensive Survey
身体性ナビゲーション(EN)を遷移・観測・融合・報酬方策構築・行動の5段階(TOFRA)で整理し、最新手法や評価指標、課題を包括的にレビューしたサーベイ。
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?
5. 議論はある?
6. 次に読むべき論文は?
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Chaoran Xiong, Yulong Huang, Fangwen Yu, Changhao Chen, Yue Wang, Songpengchen Xia, Ling Pei
分類: cs.RO
原文アブストラクト
Embodied navigation (EN) advances traditional navigation by enabling robots to perform complex egocentric tasks through sensing, social, and motion intelligence. In contrast to classic methodologies that rely on explicit localization and pre-defined maps, EN leverages egocentric perception and human-like interaction strategies. This survey introduces a comprehensive EN formulation structured into five stages: Transition, Observation, Fusion, Reward-policy construction, and Action (TOFRA). The TOFRA framework serves to synthesize the current state of the art, provide a critical review of relevant platforms and evaluation metrics, and identify critical open research challenges. A list of studies is available at https://github.com/Franky-X/Awesome-Embodied-Navigation.
