Exploring human-swarm interaction dynamics in cyber-physical systems: A physiological approach

Abstract

Complex Cyber-Physical-Human System (CPHS) integrate the human operator as an essential element to assist with different aspects of information monitoring and decision making across the system to achieve the desired goal. A crucial aspect of enhancing CPHS efficiency lies in understanding the interaction dynamics of human cognitive factors and Cyber-Physical Systems (CPS). This entails designing feedback mechanisms, reasoning processes, and compliance protocols with consideration of their psychological impacts on human operators, fostering shared awareness between humans and AI agents and calibrating feedback levels to ensure operators are informed without being overwhelmed. This study focuses on a specific CPHS scenarios involving a human operator interacting with a swarm of robots for search, rescue, and monitoring tasks. It explores the impact of swarm non-compliance rate and feedback levels from the robotic swarm on the human operators’ cognitive processes, and the extent to which individual differences in information processing influence this interaction dynamics. A human subject study with 20 participants experienced in strategic gaming involved nine scenarios with randomized robot compliance and AI feedback levels was conducted. Cognitive factors, categorized into brain-based features (mental engagement, workload, distraction) and eye-based features (pupil size, fixation, saccade, blink rate), were analyzed. Statistical analyses revealed that brain-based features, particularly mental workload, were predictive of the effect of compliance level, while feedback level and expertise affected both eye features and brain cognitive factors.