CoWear: 複数のスマートデバイスによる協調ウェアラブル慣性測位に向けて
CoWear: Towards Collaborative Wearable Inertial Localization with Multiple Smart Devices
スマートフォン・スマートウォッチ・スマートグラスの3デバイスを協調させて人の位置を推定するためのデータセットと基準フレームワークを提案し、デバイスごとの役割特化推定器と不確かさに基づく融合により精度が向上することを示した。
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著者: Zhuoyuan She, Zhanpeng Zhang, Yapeng Chen, Jiale Wang, Xin Xie, Ming Xia
分類: cs.RO
原文アブストラクト
Consumer smart devices observe the same human motion from different body locations, yet existing inertial-localization benchmarks rarely provide synchronized heterogeneous wearables with device-specific motion ground truth. We present CoWear, a dataset and reference framework for collaborative inertial localization using a smartphone, smartwatch, and smart glasses. The dataset contains over 30 participants, over 300 walking sessions, and more than 30 hours and 100 km of aggregate device trajectories, with each device individually tracked by motion capture. To enable collaboration across distinct body motions, we train role-specific estimators to predict the displacement of a common reference device over synchronized temporal windows. Their predictions are transformed to the world frame using gyroscope integration and fused according to learned uncertainty. Experiments using phone, glasses, and watch as reference targets show that multi-device fusion consistently improves both displacement and trajectory rollout accuracy over individual-device estimation. CoWear provides a dataset and reproducible baseline for studying collaborative inertial localization across heterogeneous consumer wearables.