Presentation
Measuring Trust Shifts: A Multi-Method Approach to Trust Dynamics in Cobots
SessionPoster Session 2
DescriptionMeasuring Trust Shifts: A Multi-Method Approach to Trust Dynamics in Cobots:
Trust plays a vital role in human-robot collaboration, influencing how users interact with and rely on automation. This study examines how trust shifts before and after failure events in collaborative robotics (cobots) by integrating surveys, physiological data, and behavioral observations. Participants complete an assembly task using FANUC and UR cobots, with controlled failures introduced to study trust degradation and recovery. Trust is measured through real-time physiological signals, self-reports, and behaviors such as hesitation and manual intervention. Preliminary findings reveal that trust tends to decline immediately following a failure, with varied recovery patterns based on individual differences and system responses. This work highlights the need to track trust as a dynamic, evolving process rather than a static snapshot. By combining subjective and objective measures, the study offers insights into designing more resilient human-robot systems, improving failure recovery strategies, and fostering stronger, safer collaboration between humans and intelligent systems.
Trust plays a vital role in human-robot collaboration, influencing how users interact with and rely on automation. This study examines how trust shifts before and after failure events in collaborative robotics (cobots) by integrating surveys, physiological data, and behavioral observations. Participants complete an assembly task using FANUC and UR cobots, with controlled failures introduced to study trust degradation and recovery. Trust is measured through real-time physiological signals, self-reports, and behaviors such as hesitation and manual intervention. Preliminary findings reveal that trust tends to decline immediately following a failure, with varied recovery patterns based on individual differences and system responses. This work highlights the need to track trust as a dynamic, evolving process rather than a static snapshot. By combining subjective and objective measures, the study offers insights into designing more resilient human-robot systems, improving failure recovery strategies, and fostering stronger, safer collaboration between humans and intelligent systems.
Contributor
Event Type
Poster
TimeWednesday, October 15th5:30pm - 6:30pm CDT
LocationRiverside East