Swarm Control

Swarm control research focuses on developing strategies to coordinate the collective behavior of multiple robots or agents towards a common goal, often leveraging emergent properties for enhanced efficiency and robustness. Current efforts concentrate on developing control algorithms, including those based on reinforcement learning, evolutionary neural networks, and impedance control, to manage both homogeneous and heterogeneous swarms in diverse environments, from underwater to aerial and even tabletop settings. These advancements have implications for various applications, such as environmental monitoring, infrastructure inspection, and collaborative manufacturing, while also furthering our understanding of complex systems and collective intelligence.