UAV-based systems are systems that are composed of a team of drones, various devices (like movable cameras, sensors), and human agents, which collaborate each other to accomplish defined missions. Since humans are constituent part of these systems, UAV-based systems are both mission-critical and safety-critical. Moreover, these systems are requested to operate in potentially unpredictable and unknown environments. A model of the environment describing, e.g. obstacles, no-fly zones, wind and weather conditions might be available, however, the assumption that such model is both correct and complete is often wrong. In this paper, we describe a novel approach for managing the run-time adaptation of UAV-based systems. Our approach is based on a generic collective adaptation engine that addresses collective adaptation problems in a decentralized fashion, operates at run-time, and enables the addition of new entities at any time. Moreover, our approach dynamically understands which parts of the system should be selected to solve an adaptation issue. The feasibility and scalability of the approach have been empirically evaluated in the context of a private company surveillance scenario.

Multicopters are increasingly popular since they promise to simplify a myriad of everyday tasks. Currently, vendors provide low-level APIs and basic primitives to program multicopters, making mission development a task-specific and error-prone activity. As a consequence, current approaches are affordable only for users that have a strong technical expertise. Then, software engineering techniques are needed to support the definition, development, and realization of missions at the right level of abstraction and involving teams of autonomous multicopters that guarantee the safety today's users expect. In this paper we describe a tool that enables end-users with no technical expertise, e.g., firefighters and rescue workers, to specify missions for a team of multicopters. The detailed flight plan that each multicopter must perform to accomplish the specified mission is automatically generated by preventing collisions between multicopters and obstacles, and ensuring the preservation of no-fly zones.