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    Toward realistic pursuit-evasion using a roadmap-based approach

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    Type
    Conference Paper
    Authors
    Rodriguez, Samuel
    Denny, Jory
    Burgos, Juan
    Mahadevan, Aditya
    Manavi, Kasra
    Murray, Luke
    Kodochygov, Anton
    Zourntos, Takis
    Amato, Nancy M.
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2011-05
    Permanent link to this record
    http://hdl.handle.net/10754/600046
    
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    Abstract
    In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. Our approach can be applied to more realistic scenarios than are typically studied in most previous work, including agents moving in 3D environments such as terrains, multi-story buildings, and dynamic environments. We also support more realistic three-dimensional visibility computations that allow evading agents to hide in crowds or behind hills. We demonstrate the utility of this approach on mobile robots and in simulation for a variety of scenarios including pursuit-evasion and tag on terrains, in multi-level buildings, and in crowds. © 2011 IEEE.
    Citation
    Rodriguez S, Denny J, Burgos J, Mahadevan A, Manavi K, et al. (2011) Toward realistic pursuit-evasion using a roadmap-based approach. 2011 IEEE International Conference on Robotics and Automation. Available: http://dx.doi.org/10.1109/ICRA.2011.5980467.
    Sponsors
    This research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266 by THECB NHARPaward 000512-0097-2009, by Chevron, IBM, Intel, Oracle/Sun and byAward KUS-C1-016-04, made by King Abdullah University of Science andTechnology (KAUST).
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2011 IEEE International Conference on Robotics and Automation
    DOI
    10.1109/ICRA.2011.5980467
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICRA.2011.5980467
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