Collaborative Robots Adapting Their Behavior Based on Workers’ Psychological States: A Systematic Scoping Review

Abstract

Integrating collaborative robots (cobots) in work environments is advancing rapidly, with growing attention to designing systems that can effectively collaborate with humans. A key aspect of this effort is enhancing cobots’ adaptability, that is, their ability to adjust behavior in real time based on workers’ needs and characteristics, particularly their psychological states. Despite increasing research, a synthesis of the most considered psychological states and the corresponding adaptation mechanisms is still lacking. This review examines recent experimental evidence on cobots which modify their behavior in response to workers’ psychological states and evaluates how these adaptations influence human–robot collaboration outcomes. Following preregistration on PROSPERO, this study adhered to PRISMA-P guidelines to select 23 studies focusing on cobots’ adaptation mechanisms and their impact on task performance and worker well-being. The findings reveal that most adaptations target cognitive states, particularly workload, attention, and situational awareness, reflecting a strong research emphasis on optimizing decision-making and efficiency. Emotional adaptation has been explored to a lesser extent, while real-time adjustments based on motion intention are gaining traction in movement coordination tasks. Cobots primarily rely on physiological and behavioral signals—such as heart rate variability, electrodermal activity, and gaze fixation—to infer workers’ psychological states. Various adaptation strategies, including task reallocation and speed modulation, demonstrate measurable improvements in collaboration fluency, cognitive load management, and operational performance. This review highlights the critical role of psychology in robotics research, promoting multidisciplinary collaboration to develop adaptive cobots that enhance both productivity and worker well-being.