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Toward a Myriad Robot Swarm Aggregation

Zalan Kiszli, Seongin Na, Farshad Arvin

Year
2022
Citations
4

Abstract

A new paradigm is emerging that seeks to solve real-world problems by using very large size multi-robotic systems as it attempts to close the gap between an individual robot and a cohesive group. A current challenge in swarm robotics is to connect the experience of individuals with collective determination. Aggregation of robot swarm has been studied as a mean to lead collective determination. This paper looks into a bio-inspired aggregation mechanism to investigate swarm density and estimate the collective outcome in very large swarm populations. We found that the original objective of the swarm aggregation could not be generalised and would be challenging due to barricade effect observed from experiments with large size swarms. This is very important to consider such a phenomenon that can cause problems in real-world applications of swarm robotic systems.

Keywords

Swarm behaviourSwarm roboticsRobotArtificial intelligenceComputer scienceSwarm intelligenceCollective behaviorRoboticsMechanism (biology)Particle swarm optimization

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