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        <identifier>oai:drops-oai.dagstuhl.de:2774</identifier>
        <datestamp>2024-03-06T11:09:11Z</datestamp>
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          <dc:title>Exploiting Spatial and Temporal Flexibility for Exploiting Spatial and Temporal Flexibility for Plan Execution of Hybrid, Under-actuated Systems</dc:title>
          <dc:creator>Hofmann, Andreas G.</dc:creator>
          <dc:creator>Williams, Brian C.</dc:creator>
          <dc:description>Robotic devices, such as rovers and autonomous&#13;
spacecraft, have been successfully controlled by plan&#13;
execution systems that use plans with temporal flexibility to&#13;
dynamically adapt to temporal disturbances. To date these&#13;
execution systems apply to discrete systems that abstract&#13;
away the detailed dynamic constraints of the controlled&#13;
device. To control dynamic, under-actuated devices, such&#13;
as agile bipedal walking machines, we extend this execution&#13;
paradigm to incorporate detailed dynamic constraints.&#13;
Building upon prior work on dispatchable plan execution,&#13;
we introduce a novel approach to flexible plan execution of&#13;
hybrid under-actuated systems that achieves robustness by&#13;
exploiting spatial as well as temporal plan flexibility. To&#13;
accomplish this, we first transform the high-dimensional&#13;
system into a set of low dimensional, weakly coupled&#13;
systems. Second, to coordinate these systems such that they&#13;
achieve the plan in real-time, we compile a plan into a&#13;
concurrent timed flow tube description. This description&#13;
represents all feasible control trajectories and their temporal&#13;
coordination constraints, such that each trajectory satisfies&#13;
all plan and dynamic constraints. Finally, the problem of&#13;
runtime plan dispatching is reduced to maintaining state&#13;
trajectories in their associated flow tubes, while satisfying&#13;
the coordination constraints. This is accomplished through&#13;
an efficient local search algorithm that adjusts a small&#13;
number of control parameters in real-time. The first step&#13;
has been published previously; this paper focuses on the last&#13;
two steps. The approach is validated on the execution of a&#13;
set of bipedal walking plans, using a high fidelity simulation&#13;
of a biped.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Andreas G. Hofmann and Brian C. Williams</dc:contributor>
          <dc:date>2010</dc:date>
          <dc:relation>Is Part Of Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/DagSemProc.10081.8</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-27740</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.8</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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