  We consider the positioning problem of aerial drone systems for efficient
three-dimensional (3-D) coverage. Our solution draws from molecular geometry,
where forces among electron pairs surrounding a central atom arrange their
positions. In this paper, we propose a 3-D clustering algorithm for autonomous
positioning (VBCA) of aerial drone networks based on virtual forces. These
virtual forces induce interactions among drones and structure the system
topology. The advantages of our approach are that (1) virtual forces enable
drones to self-organize the positioning process and (2) VBCA can be implemented
entirely localized. Extensive simulations show that our virtual forces
clustering approach produces scalable 3-D topologies exhibiting near-optimal
volume coverage. VBCA triggers efficient topology rearrangement for an altering
number of nodes, while providing network connectivity to the central drone. We
also draw a comparison of volume coverage achieved by VBCA against existing
approaches and find VBCA up to 40\% more efficient.
