Gazing Preference Induced Controllable Milling Behavior in Swarm Robotics

Abstract

Milling is a collective behavior that is useful in a variety of real scenarios, but how to regulate milling behavior simply and efficiently is still a challenging problem. This letter introduces a novel method for controlling milling behavior in real-world robots, where both the direction and radius of the milling pattern can be continuously adjusted by tuning a single parameter. Inspired by visual attention mechanisms, the proposed model introduces the concept of gazing preference. That is, the robot will prefer to choose a neighbor in a particular direction for interaction, which in turn creates a force that deviates from the direction of velocity and leads to the milling behavior. Additionally, a potential function ensures swarm cohesion and prevents collisions through simulated repulsive and attractive forces. Simulations and experiments involving up to 50 robots demonstrate that adjusting the gazing preference parameter enables seamless control of the rotation direction and fine-tuning of the milling pattern's angular velocity and radius. Overall, this letter provides a straightforward and effective approach for designing controlled milling behavior in swarm robotics.