Performance metrics outperform physiological indicators in robotic teleoperation workload assessment

Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation often proves unfeasible due to the diverse and intricate nature of tasks, coupled with the unpredictable hazards, and is typically prevented by stringent regulatory frameworks. Consequently, the predominant approach to managing activities in such settings remains human teleoperation. Teleoperation can be demanding, especially in high-stress situations, and involves a complex blend of both cognitive and physical workload. We present an experiment to explore a range of physiological and performance-related metrics for workload assessment during robotic teleoperation. Thirty-five participants performed a teleoperation task, during which we manipulated cognitive and physical workload conditions. We recorded multiple metrics, including brain activity using functional Near-Infrared Spectroscopy, galvanic skin responses, cardiovascular responses, subjective workload ratings, task and robot performance data. Our results suggest that robotic teleoperation performance may be the most robust metric for distinguishing between different levels of workload experienced during teleoperation, with most physiological measures becoming insignificant to distinguish high cognitive workload.

Design of an Intuitive Master for Improving Teleoperation Task Performance Using the Functional Separation of Actuators: Movement and Gravity Compensation

Teleoperation, in which humans and robots work together to improve work performance, is growing explosively. However, the work performance of teleoperation is not yet excellent. Master–slave systems with different kinematics and workspaces need space-transformation control techniques. These techniques cause psychological fatigue to an operator with poor manipulation skills. In this study, we propose an intuitive master design that focuses on fatigue. Large workspaces reduce mental fatigue; however, they lead to physical fatigue problems. To solve this problem, we reflect the role of actuators in the design, through functional separation using movement and gravity compensation. This study proposes the design and prototype fabrication of an intuitive master K-handler to improve remote-work performance. The K-handler features six degrees of freedom (DoF), an anthropomorphic structure, and a lightweight nature. It has a reach long enough to cover the workspace of the human arm to reduce mental fatigue. In addition, gravity compensation, which can reduce the operator’s physical fatigue during operation, is possible in all workspace areas.