Adaptive Interfaces and User Modeling

 

A project led by Hashini Senaratne, and supervised by Cecile Paris, Dana Kulic, David Howard, Jason Williams and Pavan Sikka

This project aims to (1) determine the optimal level of situational awareness required by a human supervisor collaborating with an autonomous multi-robot team, (2) model and estimate the optimal level of situational awareness as a continuous estimation within a dynamic team mission, (3) design and implement human-machine interface adaptations assist in maintaining one’s situational awareness to an optimal level at different stages of a dynamic team mission, and evaluate the success of dynamic situational awareness-enabled team collaboration.

In achieving these goals, Hashini and the team undertake multidisciplinary methods, e.g., conducting interview studies with human team members of human-robot collaborative applications, analysing human team member’s physiological and behavioral data (e.g., eye gaze, speech, electrocardiogram, skin conductance) collected within real and simulated human-robot collaborative applications, and conducting user evaluations within real and simulated human-robot collaborative applications with and without carefully-designed interface adaptations.