Combining Autonomous Exploration, Goal-Oriented Coordination and Task Allocation in Multi-UAV Scenarios

Successful rescue operations after big accidents or natural disasters require a fast and efficient overview of the overall situation. With recent advances, unmanned aerial vehicles (UAVs) are more and more a viable choice under such circumstances.With the number of employed UAVs, the problem of coordination arises as well as proper task allocation among possibly heterogeneous UAVs. This paper presents a hybrid approach for UAV coordination and covers the exploration of unknown terrains as well as goal-oriented coordination and simultaneous task allocation. The approach combines the simplicity of the gradient method with informed A* search and supports prioritized task assignment. The system is suited for highly dynamic environments requiring frequent path recalculations.