PACNav: Enhancing Collective Navigation for UAV Swarms in Communication-Challenged Environments

TL;DR

PACNav is a decentralized navigation method for UAV swarms that uses local observations and natural flocking behaviors to enable effective movement in communication-challenged environments, validated through simulations and real-world tests.

Contribution

It introduces the novel concepts of path persistence and path similarity for UAV swarm navigation without relying on communication or external localization.

Findings

Effective decentralized navigation demonstrated in simulations.

Successful real-world experiments in natural forest environments.

Collision avoidance integrated into the navigation approach.

Abstract

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.