Insect-inspired Visually-guided Decentralized Swarming
Mehdi Yadipour, and Imraan A. Faruque

TL;DR
This paper introduces an insect-inspired, vision-based decentralized swarming method that enables multi-agent coordination using optic flow sensing, without relying on explicit communication or position data, with proven convergence guarantees.
Contribution
It develops a novel optic flow sensing framework combined with distributed feedback for vision-guided swarming, extending Cucker-Smale flocking models with rigorous convergence analysis.
Findings
Achieved asymptotic convergence in vision-guided swarming
Developed a multi-agent optic flow sensing framework
Extended flocking models to vision-based control
Abstract
This paper addresses the need for fast, lightweight, vision-guided swarming under limited computation and no explicit communication network or position source. The study develops a multi-agent optic flow sensing framework, then integrates perfect information distributed feedback with optic flow sensing to create an analogous visually-guided feedback path for idealized inter-agent velocity and distance structures. The Cucker-Smale flocking example is used to develop vision-guided swarming with rigorous asymptotic convergence guarantees, including under ignorance of agent size.
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Taxonomy
TopicsDistributed Control Multi-Agent Systems · Robotic Path Planning Algorithms · Slime Mold and Myxomycetes Research
