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    A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems

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    ifac2017_Abdelkader.pdf
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    Type
    Article
    Authors
    Abdelkader, Mohamed cc
    Jaleel, Hassan
    Shamma, Jeff S. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Mechanical Engineering Program
    Physical Science and Engineering (PSE) Division
    RISC Laboratory
    Date
    2017-10-19
    Permanent link to this record
    http://hdl.handle.net/10754/626060
    
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    Abstract
    We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.
    Citation
    Abdelkader M, Jaleel H, Shamma JS (2017) A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems. IFAC-PapersOnLine 50: 10626–10631. Available: http://dx.doi.org/10.1016/j.ifacol.2017.08.1035.
    Sponsors
    Research supported by funding from KAUST.
    Publisher
    Elsevier BV
    Journal
    IFAC-PapersOnLine
    DOI
    10.1016/j.ifacol.2017.08.1035
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S2405896317315185
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ifacol.2017.08.1035
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Electrical and Computer Engineering Program; Mechanical Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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