  This article presents Persistence Administered Collective Navigation (PACNav)
as an approach for achieving decentralized collective navigation of Unmanned
Aerial Vehicle (UAV) swarms. The technique is inspired by the flocking and
collective navigation behavior observed in natural swarms, such as cattle
herds, bird flocks, and even large groups of humans. PACNav relies solely on
local observations of relative positions of UAVs, making it suitable for large
swarms deprived of communication capabilities and external localization
systems. We introduce the novel concepts of path persistence and path
similarity, which allow each swarm member to analyze the motion of others.
PACNav is grounded on two main principles: (1) UAVs with little variation in
motion direction exhibit high path persistence and are considered reliable
leaders by other UAVs; (2) groups of UAVs that move in a similar direction
demonstrate high path similarity, and such groups are assumed to contain a
reliable leader. The proposed approach also incorporates a reactive collision
avoidance mechanism to prevent collisions with swarm members and environmental
obstacles. The method is validated through simulated and real-world experiments
conducted in a natural forest.
