Improving Formation in Swarm Robotics with a Leader-Follower Approach

Collective Motion (CM) is a bio-inspired swarm behaviour observed in nature, such as schooling fish and flocking birds. In swarm robotics, CM is attained through the implementation of virtual viscoelastic links that generate attractive and repulsive forces among robots. This study investigates the challenges associated with maintaining formation integrity in specific geometrical arrangements, such as ring configurations. To address this, a Leader-Follower (L-F) approach is proposed to enhance the swarm shape stability. Simulation results demonstrated that the proposed method significantly optimised CM performance, achieving alignment of nearly 99% of the robots within 50 s. This shows the effectiveness of the L-F approach in successfully implementing swarm formation with a significant performance improvement.

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.1109/icma61710.2024.10633130
Citations
3
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.64
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article

Improving Formation in Swarm Robotics with a Leader-Follower Approach

Fatemeh Rekabi-Bana, Farshad Arvin, Mazen Bahaidarah, Ognjen Marjanović
3 citations
Modular Robots and Swarm Intelligence
0.64
article

Improving Formation in Swarm Robotics with a Leader-Follower Approach

Fatemeh Rekabi-Bana, Farshad Arvin, Mazen Bahaidarah, Ognjen Marjanović
article en
3 citations

Abstract

Collective Motion (CM) is a bio-inspired swarm behaviour observed in nature, such as schooling fish and flocking birds. In swarm robotics, CM is attained through the implementation of virtual viscoelastic links that generate attractive and repulsive forces among robots. This study investigates the challenges associated with maintaining formation integrity in specific geometrical arrangements, such as ring configurations. To address this, a Leader-Follower (L-F) approach is proposed to enhance the swarm shape stability. Simulation results demonstrated that the proposed method significantly optimised CM performance, achieving alignment of nearly 99% of the robots within 50 s. This shows the effectiveness of the L-F approach in successfully implementing swarm formation with a significant performance improvement.

King Abdulaziz University (SA), Durham University (GB), University of Manchester (GB)
Openalex Percentile: Top 36%
Modular Robots and Swarm Intelligence
0.64
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Improving Formation in Swarm Robotics with a Leader-Follower Approach — Fatemeh Rekabi-Bana, Farshad Arvin, et al. · (2024) | TGRS Research Map | TGRS