Human interaction experience plays a crucial role in the effectiveness of human-machine collaboration, especially as interactions in future systems progress towards tighter physical and functional integration. While automation design has been shown to impact task performance, its influence on human experience metrics such as flow, sense of agency (SoA), and embodiment remains underexplored. This study investigates how variations in automation design affect these psychological experience measures and examines correlations between subjective experience and physiological indicators. A user study was conducted in a simulated wood workshop, where participants collaborated with a lightweight robot under four automation levels. The results of the study indicate that medium automation levels enhance flow, SoA and embodiment, striking a balance between support and user autonomy. In contrast, higher automation, despite optimizing task performance, diminishes perceived flow and agency. Furthermore, we observed that grip force might be considered as a real-time proxy of SoA, while correlations with heart rate variability were inconclusive. The findings underscore the necessity for automation strategies that integrate human- centric metrics, aiming to optimize both performance and user experience in collaborative robotic systems

翻译：人机交互体验在人机协作效能中起着至关重要的作用，尤其是在未来系统中交互朝着更紧密的物理与功能集成发展的背景下。虽然自动化设计已被证明会影响任务表现，但其对人类体验指标——如心流、主体感（SoA）和具身感——的影响仍未得到充分探索。本研究探讨了自动化设计的变化如何影响这些心理体验测量，并检验了主观体验与生理指标之间的相关性。研究在一个模拟木工车间进行了一项用户研究，参与者与一台轻型机器人在四种自动化水平下进行协作。研究结果表明，中等自动化水平能提升心流、主体感和具身感，在支持与用户自主性之间取得了平衡。相比之下，更高的自动化水平尽管优化了任务表现，却降低了感知到的心流和主体感。此外，我们观察到握力可能被视为主体感的实时代理指标，而与心率变异性的相关性则尚无定论。这些发现强调了自动化策略有必要整合以人为中心的度量指标，旨在协同优化协作机器人系统的性能与用户体验。