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        <identifier>oai:drops-oai.dagstuhl.de:15442</identifier>
        <datestamp>2024-03-06T10:55:18Z</datestamp>
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          <dc:title>Connected Coordinated Motion Planning with Bounded Stretch</dc:title>
          <dc:creator>Fekete, Sándor P.</dc:creator>
          <dc:creator>Keldenich, Phillip</dc:creator>
          <dc:creator>Kosfeld, Ramin</dc:creator>
          <dc:creator>Rieck, Christian</dc:creator>
          <dc:creator>Scheffer, Christian</dc:creator>
          <dc:subject>Motion planning</dc:subject>
          <dc:subject>parallel motion</dc:subject>
          <dc:subject>bounded stretch</dc:subject>
          <dc:subject>scaled shape</dc:subject>
          <dc:subject>makespan</dc:subject>
          <dc:subject>connectivity</dc:subject>
          <dc:subject>swarm robotics</dc:subject>
          <dc:description>We consider the problem of coordinated motion planning for a swarm of simple, identical robots: From a given start grid configuration of robots, we need to reach a desired target configuration via a sequence of parallel, continuous, collision-free robot motions, such that the set of robots induces a connected grid graph at all integer times. The objective is to minimize the makespan of the motion schedule, i.e., to reach the new configuration in a minimum amount of time. We show that this problem is NP-hard, even for deciding whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a makespan of 1 can be achieved.&#13;
On the algorithmic side, we establish simultaneous constant-factor approximation for two fundamental parameters, by achieving constant stretch for constant scale. Scaled shapes (which arise by increasing all dimensions of a given object by the same multiplicative factor) have been considered in previous seminal work on self-assembly, often with unbounded or logarithmic scale factors; we provide methods for a generalized scale factor, bounded by a constant. Moreover, our algorithm achieves a constant stretch factor: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of d, then the total duration of our overall schedule is 𝒪(d), which is optimal up to constant factors.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Sándor P. Fekete and Phillip Keldenich and Ramin Kosfeld and Christian Rieck and Christian Scheffer</dc:contributor>
          <dc:date>2021</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 212, 32nd International Symposium on Algorithms and Computation (ISAAC 2021)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ISAAC.2021.9</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-154423</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2021.9</dc:identifier>
          <dc:language>eng</dc:language>
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