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        <identifier>oai:drops-oai.dagstuhl.de:22549</identifier>
        <datestamp>2025-10-02T11:05:54Z</datestamp>
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          <dc:title>Symmetry Preservation in Swarms of Oblivious Robots with Limited Visibility</dc:title>
          <dc:creator>Gerlach, Raphael</dc:creator>
          <dc:creator>von der Gracht, Sören</dc:creator>
          <dc:creator>Hahn, Christopher</dc:creator>
          <dc:creator>Harbig, Jonas</dc:creator>
          <dc:creator>Kling, Peter</dc:creator>
          <dc:subject>Swarm Algorithm</dc:subject>
          <dc:subject>Swarm Robots</dc:subject>
          <dc:subject>Distributed Algorithm</dc:subject>
          <dc:subject>Pattern Formation</dc:subject>
          <dc:subject>Limited Visibility</dc:subject>
          <dc:subject>Oblivious</dc:subject>
          <dc:description>In the general pattern formation (GPF) problem, a swarm of simple autonomous, disoriented robots must form a given pattern. The robots' simplicity imply a strong limitation: When the initial configuration is rotationally symmetric, only patterns with a similar symmetry can be formed [Masafumi Yamashita and Ichiro Suzuki, 2010]. The only known algorithm to form large patterns with limited visibility and without memory requires the robots to start in a near-gathering (a swarm of constant diameter) [Christopher Hahn et al., 2024]. However, not only do we not know any near-gathering algorithm guaranteed to preserve symmetry but most natural gathering strategies trivially increase symmetries [Jannik Castenow et al., 2022]. &#13;
Thus, we study near-gathering without changing the swarm’s rotational symmetry for disoriented, oblivious robots with limited visibility (the OBLOT-model, see [Paola Flocchini et al., 2019]). We introduce a technique based on the theory of dynamical systems to analyze how a given algorithm affects symmetry and provide sufficient conditions for symmetry preservation. Until now, it was unknown whether the considered OBLOT-model allows for any non-trivial algorithm that always preserves symmetry. Our first result shows that a variant of Go-To-The-Average always preserves symmetry but may sometimes lead to multiple, unconnected near-gathering clusters. Our second result is a symmetry-preserving near-gathering algorithm that works on swarms with a convex boundary (the outer boundary of the unit disc graph) and without "holes" (circles of diameter 1 inside the boundary without any robots).</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Raphael Gerlach and Sören von der Gracht and Christopher Hahn and Jonas Harbig and Peter Kling</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 324, 28th International Conference on Principles of Distributed Systems (OPODIS 2024)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.OPODIS.2024.13</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-225490</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2024.13</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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