Identifying Hazardous Emerging Behaviors in Search and Rescue Missions with Drones: A Proposed Methodology

Abstract

Search and rescue (SAR) teams are trained to swiftly act and operate in a feasible way, so as to reduce the risk of death associated with accidents due to natural and manmade disasters, as well as during recreational or sports activities such as swimming, climbing and hiking. In this context, SAR teams test emergent and rapidly evolving technologies to evaluate their usefulness in different operational scenarios and to assess if these technologies can increase their effectiveness. Unmanned Aerial Vehicles (UAVs) are examples of such technologies. UAVs are agile, fast and can exhibit autonomous behavior. Therefore, there is a need to assess their usefulness and learn their limitations aiming at comprehending under which settings and contexts can seamlessly collaborate with SAR teams. In our ongoing research, we have designed and implemented an autonomous UAV platform suitable for rescue and life-saving services, namely the ROLFER (Robotic Lifeguard For Emergency Rescue) platform. With a view to assess its operational behavior, as well as of other systems of similar characteristics, in cases where unwanted and adverse events occur during its operation, a new methodology is being proposed in this paper. The proposed methodology combines, in novel way, existing methods from different domains aiming at identifying the states and conditions under which the combined SAR and UAV system could fail. The methodology aims to support SAR teams in deciding if the UAV is appropriate tool to be used in the context of an emergency.