3D Robotic Swarmalators That Reconfigure, Navigate, and Avoid Obstacles

Abstract

We realize 3D robotic swarmalators that reconfigure, navigate, and avoid obstacles with formal safety on Crazyflie drones. We incorporate ellipsoidal Control Barrier Functions to avoid downwash turbulence between drones, and a combination of Control Lyapunov Function and Control Barrier Function methods to enable the collective to move toward desired locations while avoiding collisions between drones or with nearby obstacles. We implement a global control scheme that moves the collective as a single entity, and a local control scheme that enables fluid-like flow around nearby obstacles while maintaining the same general collective formation. Finally, we demonstrate how the swarmalator model combined with these control schemes can be used to reconfigure and rotate a drone collective so it moves through a narrow passage without colliding with the surrounding environment. Our simulations and physical experiments quantify scalability limits and validate the feasibility of implementing 3D swarmalator-based control on real drone collectives.