WILDCAT
The use of remotely controlled robots is proliferating in support of (pre-)first responders during disaster management. Most attention is focused on the response phase, when robots e.g. can traverse difficult terrain. However, there are also substantial benefits to be gained through the use of this technology during the prevention/mitigation, preparedness and recovery phases.
WILDCAT targets the common challenge of providing situational awareness to reduce the risk posed to (pre-)first responders by unavoidable emergencies through the opportunities provided by sensor platforms for sharing risk information mounted on autonomous or remotely controlled robots. Specifically the objective of the project is to advance best practice concerning the sharing of fine-grained terrain maps for risks that are not trivial to identify, but rather fraught with high uncertainty. An example of this involves threats to (critical) infrastructure, e.g., roads and high voltage power lines, due to wildfires, for which ignition and spread models are understudied and under much debate.
This approach of WILDCAT is to address this objective from a technology and policy perspective. From a technology perspective WILDCAT will analyse and describe the tools available, from sensors to visualisations, to communicate complex risks through fine-grained terrain maps (with a focus on wildfires). This will allow (pre-)first responders to better understand and handle threats. From a policy perspective WILDCAT will further develop a relevant Disaster Scenarios Analysis Framework (DSAF) to allow the deployment of this technology considering local traditions and conditions during disaster management. This will allow strategic decision-makers to describe how to increase preparedness for a large, constantly expanding set of societal risks.
The project is led by KTH Royal Institute of Technology in cooperation with the National Aerospace University in Ukraine (KhAI) and SAHER (Europe) in Estonia.
