Assessing Trust in Collaborative Robotics with Different Human-Robot Interfaces

Human-robot interfaces (HRIs) serve as the main communication tools for controlling and programming robots in industry 4.0 applications. To be effective, the design of these interfaces should consider not only functional and morphological characteristics, but also factors influencing human interactions, such as trust. A lack of trust is linked to the underutilization or misuse of collaborative robots, leading to ineffective automation implementation and compromised safety. The assessment of human factors is therefore gaining traction in robotics, with the emergence of both objective and subjective methodologies. Nevertheless, the absence of a holistic approach hinders the development of a unified assessment framework. This study introduces a novel assessment methodology that integrates self-reporting questionnaires with human-centric data collected through wearable sensing technologies. The approach aims to offer a comprehensive evaluation of HRIs, considering both perceptual and behavioral dimensions. Empirical testing on three different HRIs substantiates the effectiveness of this methodology. Preliminary results reveal variations in trust levels based on the combination of tasks performed and the specific HRI used for communication with a collaborative robot. These findings not only contribute to advancing our understanding of trust dynamics in human-robot interactions but also lay the groundwork for a more inclusive evaluation framework, enhancing our comprehension of the intricate interplay between humans and robots in the context of smart manufacturing.