Adaptive Task Reallocation for Lunar Exploration: Cognitive Load Management in VR to Enhance Human-Computer Collaboration

In lunar exploration, astronauts' cognitive load critically impacts the efficacy of Human-Computer Collaboration (HCC). Effective management of cognitive load is essential for lunar mission success. Current research on HCC cognitive load primarily focuses on post-hoc evaluation, failing to leverage real-time assessment and quantitative outcomes, thus misaligning with actual mission demands. Given the interdependence between machine intelligence levels and astronauts' cognitive states, this study proposes an innovative Virtual Reality (VR)-based training system. Centered on three prototypical lunar missions, the system dynamically adjusts task difficulty and machine intelligence levels based on real-time cognitive load monitoring, deliberately exposing astronauts to varying cognitive stress levels. State-of-the-art sensors continuously capture multimodal physiological data (e.g., GSR, HR, SpO₂), enabling real-time task reallocation through an adaptive system. This VR framework holistically addresses multifactorial influences on astronauts' HCC performance in complex lunar environments, establishing a closed-loop integration of physiological data acquisition, cognitive load evaluation, intelligence level modulation, and task difficulty adjustment. By advancing a novel paradigm for optimizing HCC efficiency, this work lays a critical foundation for future lunar exploration in high-demand settings.