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Unmanned aerial vehicles (UAVs) are becoming vital warfare and homeland security platforms because they have the potential to significantly reduce cost and risk to human life while amplifying warfighter and first-responder capabilities. This article builds on the very active area of planning and control for autonomous multiagent systems. This work represents a step toward enabling robust decision making for distributed autonomous UAVs by improving the team's operational reliability and capabilities through better system self-awareness and adaptive mission planning. The health-aware task assignment algorithm developed in this article was demonstrated to be effective both in simulation and flight experiments.