Principal Investigator: Ali Abbas
Other Researchers: Dusan Stipanovic, Alexander Zatezalo
The purpose of this research is to provide a fundamentally new approach for maximizing the utility of multiple objectives given limited resources in homeland security applications. This particular effort will focus on the design of multi-objective decision strategies for groups of unmanned vehicles for applications in border protection and in search and rescue missions using a mix of control theory and multiattribute utility theory. This work can also be applied in coast guard patrol applications where the objective is to increase surveillance coverage given limited vessels and man power. It can also be applied to screening of cargo given limited resources. In addition, it can be applied during search and rescue missions in the event of bioterror attacks. Finally, it can be applied to determine optimal defense strategies in the presence of multiple simultaneous attacks. The new strategies will enable vehicles (or defenders in case of attacker-defender models) to make autonomous, fast and accurate normative decisions based on large amounts of data which may be incomplete (or corrupted by noise or human inefficiencies). While accomplishing multiple objectives such as surveillance, target recognition and tracking, the vehicles must avoid collisions and keep the communication links reliable at all times.