PACNav: 通信困難環境におけるUAV群の集合ナビゲーション強化
PACNav: Enhancing Collective Navigation for UAV Swarms in Communication-Challenged Environments
通信や外部測位が使えない環境で、UAV群が局所観測のみから群れのリーダーを推定し、衝突回避しつつ森の中でも集合的に飛行できる分散ナビゲーション手法を提案・実証した。
著者: Afzal Ahmad, Daniel Bonilla Licea, Giuseppe Silano, Tomas Baca, Martin Saska
分類: cs.RO
原文アブストラクト
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.
