Collective Dynamics of Intelligent Active Brownian Particles with Visual Perception and Velocity Alignment in 3D: Spheres, Rods, and Worms
Zhaoxuan Liu, Marjolein Dijkstra

TL;DR
This paper uses computer simulations to explore how intelligent active Brownian particles with visual perception and velocity alignment behave in 3D, revealing diverse collective patterns like clustering, milling, and band formations.
Contribution
It introduces a comprehensive simulation study of 3D intelligent active Brownian particles with visual perception and velocity alignment, highlighting new collective behaviors and structures.
Findings
Spherical iABPs form clusters, worms, and milling patterns.
Rod-like iABPs create band-like, worm-like, and helical structures.
Various patterns resemble natural collective behaviors like fish baitballs and ant milling.
Abstract
Many living systems, such as birds and fish, exhibit collective behaviors like flocking and swarming. Recently, an experimental system of active colloidal particles has been developed, where the motility of each particle is adjusted based on its visual detection of surrounding particles. These particles with visual-perception-dependent motility exhibit group formation and cohesion. Inspired by these behaviors, we investigate intelligent active Brownian particles (iABPs) equipped with visual perception and velocity alignment in three dimensions using computer simulations. The visual-perception-based self-steering describes the tendency of iABPs to move toward the center of mass of particles within their visual cones, while velocity alignment encourages alignment with neighboring particles. We examine how the behavior varies with the visual cone angle theta, self-propulsion speed (Peclet…
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Micro and Nano Robotics · Robotic Path Planning Algorithms
