Clustering Activities using Regional Reasoning

may be realized. The approach to clustering activities described in this paper defines a set of regions to satisfy all activities and their associated constraints, while modeling risk in the battlespace to avoid sending the UAVs to non-survivable areas. The software requirements for regional representation, algorithms that may be used to solve the inherent set covering problem, and the advantages of our approach are discussed. Unmanned Air Vehicles (UAVs), such as Joint Unmanned Combat Air Systems (J-UCAS), will be tasked to perform a variety of activities, including weapon releases and imaging tasks, during Suppression of Enemy Air Defense (SEAD), Reconnaissance, and other military relevant missions. Given each target’s location and eective weapon and sensor ranges, each activity may be performed within a variety of regions specific to it. By considering a “cluster” of activities which may be executed from a common region, a number of mission eciencies may be realized, as described below. The approach to clustering activities described in this paper defines a set of regions to satisfy all activities and their associated constraints, while modeling risk in the battlespace to avoid sending the UAVs to non-survivable areas. Clustering activities provides a number of benefits from a Concept of Operations (CONOPS) and tactical perspective. Eciency may be gained by reducing the UAVs’ travel time to multiple activity execution