Mission Planning for Shepherding a Swarm of Uninhabited Aerial Vehicles

Abstract

AbstractUninhabited aerial vehicles (UAVs) are widely used in many areas for completing complex missions such as tracking targets, search and rescue, farming (shepherding in the traditional sense) and mapping. Mission planning for shepherding a UAV swarm is advantageous for Human-Swarm Teaming. While most research on shepherding see the shepherd as a simple reactive agent, a smart shepherd in a complex environment will need to consider many dimensions and sub-decisions to successfully guide a swarm through complex environment and towards a goal.In this chapter, we review and offer formal definitions for the sub-problems required for a shepherd to complete a mission successfully. The swarm mission planning system needs to have decision modules capable of solving four main problems: task decomposition, task assignment, path planning and trajectory generation. These sub-problems are coupled differently depending on the scenario. This chapter defines these sub-problems in their general form and gives UAV swarm shepherding problem as a specific application. A brief review of the widely used algorithms for tackling these problems and the state of art of mission planning are also given in this chapter.KeywordsUninhabited aerial vehiclesMission planningTask assignmentEvolutionary algorithms