Trajectories of short-term operator adaptation in cobot-assisted disassembly: a within-subject multimodal analysis

Abstract

Collaborative robots are increasingly deployed in Industry 5.0 disassembly cells, yet how operators adapt across repeated cobot interactions is rarely characterised multimodally. The Day-2 axis of the MultiPhysio-HRC corpus was analysed: forty-two participants performed up to five repetitions each of a Fanuc CRX-20 cobot-assisted disassembly and a matched manual control, with 12-channel dry EEG, ECG, EDA, EMG and respiration recorded throughout; primary inference was based on the paired-analysis cohort (n = 39, ≥ 3 repetitions per context). Mixed-effects models and per-subject physiological regressions revealed a within-subject adaptation signature confined to cobot: state anxiety, workload, frustration and arousal declined while dominance grew, whereas manual produced flat or worsening trajectories. Repeated-measures analyses showed stronger aggregate physiological–state coupling during cobot than manual work (subject-level permutation p ≈ .001), although no individual channel showed a reliable context-specific effect. Cross-subject prediction of individual adaptation slopes was largely unsuccessful.