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Quotient Geometry and Persistence-Stable Metrics for Swarm Configurations

arXiv:2603.18041v1 Announce Type: new Abstract: Swarm and constellation reconfiguration can be viewed as motion of an unordered point configuration in an ambient space. Here, we provide persistence-stable, symmetry-invariant geometric representations for comparing and monitoring multi-agent configuration data. We introduce a quotient formation space $\mathcal{S}_n(M,G)=M^n/(G\times S_n)$ and a formation matching metric $d_{M,G}$ obtained by optimizing a worst-case assignment error over ambient symmetries $g\in G$ and relabelings $\sigma\in S_n$. This metric is a structured, physically interpretable relaxation of Gromov--Hausdorff distance: the induced inter-agent metric spaces satisfy $d_{\mathrm{GH}}(X_x,X_y)\le d_{M,G}([x],[y])$. Composing this bound with stability of Vietoris--Rips persistence yields $d_B(\Phi_k([x]),\Phi_k([y]))\le d_{M,G}([x],[y])$, providing persistence-stable signatures for reconfiguration monitoring. We analyze the metric geometry of $(\mathcal{S}_n(M,G),d_{M,

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Mark M. Bailey
· · 1 min read · 9 views

arXiv:2603.18041v1 Announce Type: new Abstract: Swarm and constellation reconfiguration can be viewed as motion of an unordered point configuration in an ambient space. Here, we provide persistence-stable, symmetry-invariant geometric representations for comparing and monitoring multi-agent configuration data. We introduce a quotient formation space $\mathcal{S}_n(M,G)=M^n/(G\times S_n)$ and a formation matching metric $d_{M,G}$ obtained by optimizing a worst-case assignment error over ambient symmetries $g\in G$ and relabelings $\sigma\in S_n$. This metric is a structured, physically interpretable relaxation of Gromov--Hausdorff distance: the induced inter-agent metric spaces satisfy $d_{\mathrm{GH}}(X_x,X_y)\le d_{M,G}([x],[y])$. Composing this bound with stability of Vietoris--Rips persistence yields $d_B(\Phi_k([x]),\Phi_k([y]))\le d_{M,G}([x],[y])$, providing persistence-stable signatures for reconfiguration monitoring. We analyze the metric geometry of $(\mathcal{S}_n(M,G),d_{M,G})$: under compactness/completeness assumptions on $M$ and compact $G$ it is compact/complete and the metric induces the quotient topology; if $M$ is geodesic then the quotient is geodesic and exhibits stratified singularities along collision and symmetry strata, relating it to classical configuration spaces. We study expressivity of the signatures, identifying symmetry-mismatch and persistence-compression mechanisms for non-injectivity. Finally, in a phase-circle model we prove a conditional inverse theorem: under semicircle support and a gap-labeling margin, the $H_0$ signature is locally bi-Lipschitz to $d_{M,G}$ up to an explicit factor, yielding two-sided control. Examples on $\mathbb{S}^2$ and $\mathbb{T}^m$ illustrate satellite-constellation and formation settings.

Executive Summary

The article 'Quotient Geometry and Persistence-Stable Metrics for Swarm Configurations' presents a novel approach to comparing and monitoring multi-agent configuration data in swarm reconfiguration and constellation reconfiguration. The authors introduce a quotient formation space and a formation matching metric, which provide persistence-stable and symmetry-invariant geometric representations. This approach allows for structured and physically interpretable comparisons of complex configurations. The authors also analyze the metric geometry of the quotient space and study the expressivity of the signatures, identifying mechanisms for non-injectivity. The article concludes with a conditional inverse theorem and examples illustrating satellite-constellation and formation settings.

Key Points

  • Introduction of quotient formation space and formation matching metric for comparing multi-agent configuration data
  • Persistence-stable and symmetry-invariant geometric representations
  • Analysis of metric geometry of the quotient space and study of expressivity of signatures

Merits

Strength in geometric representation

The introduction of a quotient formation space and a formation matching metric provides a structured and physically interpretable approach to comparing complex configurations.

Advancements in persistence-stable metrics

The authors' approach provides persistence-stable and symmetry-invariant geometric representations, addressing a significant challenge in comparing multi-agent configuration data.

Analytical tools for metric geometry

The authors' analysis of the metric geometry of the quotient space provides a deeper understanding of the structure and properties of the space.

Demerits

Technical complexity

The article assumes a high level of mathematical background, which may limit accessibility to researchers without a strong foundation in geometry and topology.

Limited applicability

The approach may not generalize to all types of swarm configurations or constellations, limiting its practical applicability.

Expert Commentary

This article makes a significant contribution to the field of swarm robotics and multi-agent systems by providing a novel approach to comparing and monitoring complex configurations. The introduction of persistence-stable and symmetry-invariant geometric representations addresses a significant challenge in the field and has the potential to facilitate decision-making and inform policy decisions. The analytical tools developed for the metric geometry of the quotient space provide a deeper understanding of the structure and properties of the space, which is essential for understanding the behavior of complex systems. However, the technical complexity of the article may limit accessibility to researchers without a strong foundation in geometry and topology.

Recommendations

  • Researchers in swarm robotics and multi-agent systems should consider adapting the approach to other types of swarm configurations or constellations.
  • Future research should focus on developing more accessible and user-friendly versions of the approach, as well as exploring its applicability to other fields such as biology and material science.

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