User Modelling of Situational Awareness Inefficiencies

 

Towards User-Adaptive Assistance to Maintain Optimal Dynamic Situational Awareness during Human-Robot Collaboration

A project led by Hashini Senaratne, in collaboration with Cécile Paris, Dana Kulić, David Howard, Jason Williams, Pavan Sikka and Leimin Tian.

This project aims to (1) determine the optimal level of situational awareness required by a human supervisor collaborating with an autonomous multi-robot team, and (2) model and estimate the optimal level of situational awareness as a continuous estimation within a dynamic team mission. In the future, we plan to utilise the user models developed to design and implement human-machine interface adaptations. The aim is to assist human operators in maintaining situational awareness at an optimal level during a dynamic team mission. This dynamic situational awareness-enabled team collaboration is expected to improve team performance.

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 behavioural 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.

As a postdoc of CINTEL FSP from 2022 to 2024, Hashini led the research and activities of this project covering the following outputs, and she is continuing to progress this research as a research scientist at CSIRO’s Robotic Design and Interaction group.

Project Outcomes: