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Task Structure and Scalability in Multi-Robot Authoring

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arXiv:2610.22670v1 Announce Type: new Abstract: Multi-robot authoring can reduce completion time by distributing drawing work, but the resulting speedup depends on task structure and the allocation-routing pipeline. We investigate these relationships by representing drawings as geometric stroke graphs and comparing component-level (single-token) allocation with shared-token (decomposed) allocation, which permits multiple robots to work within a connected component. A simulation study of 385 drawings and teams of one to eight robots shows diminishing speedup gains under single-token allocation and larger mean speedups under the shared-token pipeline, each normalized by its own single-robot completion time. Shared-token execution also exhibits lower idle-time shares at larger team sizes, al…

SourcearXiv RoboticsAuthor: Christian Marowski, Byung-Cheol Min
Task Structure and Scalability in Multi-Robot Authoring
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[Submitted on 15 Oct 2026]

Title:Task Structure and Scalability in Multi-Robot Authoring

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Abstract:Multi-robot authoring can reduce completion time by distributing drawing work, but the resulting speedup depends on task structure and the allocation-routing pipeline. We investigate these relationships by representing drawings as geometric stroke graphs and comparing component-level (single-token) allocation with shared-token (decomposed) allocation, which permits multiple robots to work within a connected component. A simulation study of 385 drawings and teams of one to eight robots shows diminishing speedup gains under single-token allocation and larger mean speedups under the shared-token pipeline, each normalized by its own single-robot completion time. Shared-token execution also exhibits lower idle-time shares at larger team sizes, although it does not reduce completion time for every drawing. Comparisons across structural attribute groups reveal associations between structural descriptors and differences in scaling behavior, with greater separation between several attribute groups at larger team sizes. These findings characterize empirical scaling in the evaluated pipelines and highlight the importance of considering within-component workload and graph structure alongside component count. Additional materials are available at this https URL.

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Robotics (cs.RO)

Cite as: arXiv:2610.22670 [cs.RO]

(or arXiv:2610.22670v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.22670

arXiv-issued DOI via DataCite (pending registration)

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From: Christian Marowski [view email] [v1] Thu, 15 Oct 2026 21:37:50 UTC (1,634 KB)

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  • AI generation is temporarily unavailable; this entry was preserved with deterministic fallback metadata.
  • arXiv:2610.22670v1 Announce Type: new Abstract: Multi-robot authoring can reduce completion time by distributing drawing work, but the resulting speedup depends on task structure…

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