Modeling collective behaviors from optic flow and retinal cues
Diego Castro, Franck Ruffier, Christophe Eloy
Abstract
Animal collective behavior is often modeled with self-propelled particles, assuming each individual has “omniscient” knowledge of its neighbors. Yet, neighbors may be hidden from view and we do not know the effect of this information loss. To address this question, we propose a visual model of collective behavior where each particle moves according to bioplausible visual cues, in particular the optic flow. This visual model successfully reproduces three classical collective behaviors: swarming, schooling, and milling. This model offers a potential solution for controlling artificial swarms visually. Published by the American Physical Society 2024
Topics & Concepts
Collective behaviorComputer scienceFlocking (texture)Artificial intelligenceSensory cueFlow (mathematics)Animal behaviorHuman–computer interactionCognitive psychologyCommunicationPsychologyPhysicsMechanicsBiologySociologyQuantum mechanicsZoologyAnthropologyDistributed Control Multi-Agent SystemsMicro and Nano RoboticsNeural dynamics and brain function