Michael Schwung

The complexities of decision-making in drone airlines prove to be pivotal and challenging as the dynamic environment introduces variability and many decisions are conventionally static. This paper introduces an advanced decision-making system designed for the multifaceted landscape of drone applications. Our proposed system addresses various aspects, including drone assignment, safety zone sizing, priority determination, and more. The scoring model enhances adaptability in real-time scenarios, particularly highlighted by the dynamic adjustment. Based on the scenario concerning the definition of the safety zone, we have successfully applied this method and evaluated all potential scores. The user-friendly and intuitive configuration further augments the system’s accessibility, facilitating efficient deployment. In essence, the proposed system stands as an innovative approach with decision-making paradigms in the dynamic landscape of drone operations.

This paper proposes an event-based method for the cooperative control of two mobile objects (agents). The aim is to plan online collision-free trajectories locally for the agents and to follow these trajectories even under the influence of external disturbances. The method is able to react to changes of the trajectory of the nearby agent. It uses only locally measured data and information, which is sent over an unreliable communication network and may be delayed or lost. The agents are divided into a stand-on agent and a give-way agent. The first agent follows its trajectory, which may be changed to avoid collisions with static obstacles. The second agent has to avoid a collision with the first agent. To this aim, a control unit is used that executes four tasks: Estimation of the current network properties, prediction of the movement of the stand-on agent, invocation of communication, planning of collision-free trajectories. A simulation study with two quadrotors illustrates the operating principle of the method.