TacCap: 人間からロボットへの技能転移を可能にするウェアラブルFBG触覚センサ
TacCap: A Wearable FBG-Based Tactile Sensor for Seamless Human-to-Robot Skill Transfer
Fiber Bragg Gratingを用いた軽量・耐久性のあるウェアラブル触覚センサTacCapを開発し、人間の把持データをロボットへ転移できることを把持安定性予測で示した論文。
著者: Chengyi Xing, Hao Li, Yi-Lin Wei, Tian-Ao Ren, Tianyu Tu, Yuhao Lin, Elizabeth Schumann, Wei-Shi Zheng, Mark R. Cutkosky
分類: cs.RO
原文アブストラクト
Tactile sensing is essential for dexterous manipulation, yet large-scale human demonstration datasets lack tactile feedback, limiting their effectiveness in skill transfer to robots. To address this, we introduce TacCap, a wearable Fiber Bragg Grating (FBG)-based tactile sensor designed for seamless human-to-robot transfer. TacCap is lightweight, durable, and immune to electromagnetic interference, making it ideal for real-world data collection. We detail its design and fabrication, evaluate its sensitivity, repeatability, and cross-sensor consistency, and assess its effectiveness through grasp stability prediction and ablation studies. Our results demonstrate that TacCap enables transferable tactile data collection, bridging the gap between human demonstrations and robotic execution. To support further research and development, we open-source our hardware design and software.
