リアルタイム適応型産業用ロボット：人とロボットの協働における安全性と快適性の向上
Real-Time Adaptive Industrial Robots: Improving Safety And Comfort In Human-Robot Collaboration
作業者の瞳孔径や距離をリアルタイムに計測し、ロボットの速度や動きを適応させることで、認知負荷を下げ快適性・安全性・信頼感を高めるシステムを提案し、ユーザー研究で有効性を示した。
著者: Damian Hostettler, Simon Mayer, Jan Liam Albert, Kay Erik Jenss, Christian Hildebrand
分類: cs.RO
原文アブストラクト
Industrial robots become increasingly prevalent, resulting in a growing need for intuitive, comforting human-robot collaboration. We present a user-aware robotic system that adapts to operator behavior in real time while non-intrusively monitoring physiological signals to create a more responsive and empathetic environment. Our prototype dynamically adjusts robot speed and movement patterns while measuring operator pupil dilation and proximity. Our user study compares this adaptive system to a non-adaptive counterpart, and demonstrates that the adaptive system significantly reduces both perceived and physiologically measured cognitive load while enhancing usability. Participants reported increased feelings of comfort, safety, trust, and a stronger sense of collaboration when working with the adaptive robot. This highlights the potential of integrating real-time physiological data into human-robot interaction paradigms. This novel approach creates more intuitive and collaborative industrial environments where robots effectively 'read' and respond to human cognitive states, and we feature all data and code for future use.
