2025/12/02 by Chiara Calascibetta, Calascibetta, Chiara, Laëtitia Giraldi +3
Computer Science · Engineering · Physics and Astronomy · #Distributed Control Multi-Agent Systems #FOS: Physical sciences #Micro and Nano Robotics #Modular Robots and Swarm Intelligence #Soft Condensed Matter (cond-mat.soft)
paper · pdf · doi:10.48550/arxiv.2512.02627
openalex publication_date 2025/12/02 · openalex created_date 2025/12/04 · openalex updated_date 2026/07/28
This study investigates the use of global control strategies to enhance the directed migration of swarms of interacting self-propelled particles confined in a channel. Uncontrolled dynamics naturally leads to wall accumulation, clogging, and band formation due to the interplay between self-organization and confinement. This work explores whether a uniform global control, such as magnetic field acting on all particles, can optimize collective transport. Using a discrete Vicsek-like model, it is found that simple global alignment controls, optimized via reinforcement learning, efficiently suppress unfavorable configurations and significantly increase the net particle flux along a prescribed channel direction. These results highlight that coarse, system-level observations are sufficient to achieve near-optimal control, even in regimes with strong fluctuations or partial ordering.