Agent-based Simulation for UAV Swarm Mission Planning and Execution

Swarms of Unmanned Aerial Vehicles (UAV) have been foreseen by multiple organizations to serve an important role in future air-based warfare and civilian operations. UAVs are less expensive than their piloted counterparts, provide greater flexibilities and remove the need for on-board pilot support. Efficient control of swarms opens a set of new challenges, such as automatic UAV coordination, efficient swarm monitoring and dynamic mission planning. In this paper, we investigate the problem of dynamic mission planning for a UAV swarm. An agent-based control framework is proposed, which employs a control agent for task assignment and multiple UAV agents for local task scheduling. A prototype simulation framework is implemented as a proof-of-concept. Experimentation with the framework suggests the effectiveness of swarm control using several mission planning mechanisms.