Dynamic Density-Guided Method for Multi-Robot Formation Transformation

This paper addresses the formation control problem for ground mobile robot formations and proposes a formation transition method based on dynamic density guidance. To achieve different formation transitions, a centroidal Voronoi tessellations (CVT) formation control algorithm is utilized to avoid collisions during the transition process. By leveraging the properties of the CVT algorithm, a dynamic density is generated by constructing a transition density function between the initial formation density function and the desired density function. The CVT algorithm then guides the robots in the formation to move and complete the transition and reconstruction of the formation. The simulation results demonstrate that, compared to using the desired density function directly, this method not only successfully resolves certain formation transition failures but also reduces the average positional error of the formation during the transition process.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-11-01
DOI
https://doi.org/10.16183/j.cnki.jsjtu.2024.209
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
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article

Dynamic Density-Guided Method for Multi-Robot Formation Transformation

SHILAP Revista de lepidopterología
Distributed Control Multi-Agent Systems
article

Dynamic Density-Guided Method for Multi-Robot Formation Transformation

article en

Abstract

This paper addresses the formation control problem for ground mobile robot formations and proposes a formation transition method based on dynamic density guidance. To achieve different formation transitions, a centroidal Voronoi tessellations (CVT) formation control algorithm is utilized to avoid collisions during the transition process. By leveraging the properties of the CVT algorithm, a dynamic density is generated by constructing a transition density function between the initial formation density function and the desired density function. The CVT algorithm then guides the robots in the formation to move and complete the transition and reconstruction of the formation. The simulation results demonstrate that, compared to using the desired density function directly, this method not only successfully resolves certain formation transition failures but also reduces the average positional error of the formation during the transition process.

SHILAP Revista de lepidopterología
University of California, Merced (US), Xi'an Technological University (CN)
Sustainable cities and communities
Openalex Percentile: Top 62%
Distributed Control Multi-Agent Systems
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Dynamic Density-Guided Method for Multi-Robot Formation Transformation · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS