  In this paper, we simulated a distributed, cooperative path planning
technique for multiple drones (~200) to explore an unknown region (~10,000
connected units) in the presence of obstacles. The map of an unknown region is
dynamically created based on the information obtained from sensors and other
drones. The unknown area is considered a connected region made up of hexagonal
unit cells. These cells are grouped to form larger cells called sub-areas. We
use long range and short range communication. The short-range communication
within drones in smaller proximity helps avoid re-exploration of cells already
explored by companion drones located in the same subarea. The long-range
communication helps drones identify next subarea to be targeted based on
weighted RNN (Reverse nearest neighbor). Simulation results show that weighted
RNN in a hexagonal representation makes exploration more efficient, scalable
and resilient to communication failures.
