Many missions are deemed dangerous or impractical to perform by humans, but can use collaborating, self-managing Unmanned Autonomous Vehicles (UAVs) which adapt their behaviour to current context, recover from component failure or optimise performance. This paper describes a policy-based distributed self-management framework for both individual and teams of UAVs. We use three levels of specifications --- policy, mission class and mission instance to enable reuse of both policies and mission classes. The architecture has been tested on devices ranging from small laptops to body area networks. Initial evaluation shows the distributed architecture is scalable and outperforms a centralised mission management scheme.