Multi Robot Flocking

Multi-robot flocking research focuses on designing algorithms that enable groups of robots to move cohesively, avoiding collisions while maintaining desired formations. Current efforts explore various control strategies, including those based on bio-inspired models (like Reynolds' boids rules), predictive control using potential fields or Gibbs Random Fields, and constraint-driven approaches prioritizing energy efficiency or specific formations (e.g., V-formation). This field is significant for its potential applications in diverse areas such as search and rescue, environmental monitoring, and even entertainment, driving advancements in distributed control, human-robot interaction, and the development of robust and adaptable multi-agent systems.