Support for Resilience in Human-Robot USAR Teams

Abstract

Urban search and rescue (USAR) teams often work in a dangerous, stressful and unpredictable environment. Danger can be partly solved by using robots, as these can reach places too dangerous for men. Humans working with these robots require effective collaboration in performing rescue tasks. In an unpredictable environment like with USAR a good distribution of tasks among the members of a rescue team is of great importance. A dynamic task allocation approach would suit the needs of an USAR team, as members of the team should be quickly reassigned if need be. Workflows have been a favourable approach to model task allocation, yet they often remain static. This research project will look into methods for creating dynamic workflows to support task allocation and provide the means for an effective human-robot collaboration in USAR.