Core Concepts
A bioinspired decentralized approach for collective navigation of UAV swarms that relies solely on onboard sensors and computational resources, without the need for communication or global localization capabilities.
Abstract
The paper introduces Persistence Administered Collective Navigation (PACNav), a decentralized approach for the collective navigation of UAV swarms in communication-challenged environments. The method is inspired by the flocking and collective navigation behavior observed in natural swarms, such as cattle herds, bird flocks, and human groups.
PACNav relies on local observations of relative positions of UAVs, making it suitable for large swarms deprived of communication capabilities and external localization systems. The key concepts introduced are:
Path Persistence: UAVs with little variation in motion direction exhibit high path persistence and are considered reliable leaders by other UAVs.
Path Similarity: 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 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 environment, demonstrating the potential of UAV swarms for real-world applications beyond "toy scenarios".