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    Simulation Platform for the Evaluation of Robotic Swarm Algorithms

    155587_155587.pdf (276.5Kb)
    Access Status
    Open access
    Authors
    Ortega-Sanchez, Cesar
    Hamer, M.
    Date
    2010
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Hamer, M. and Ortega-Sanchez, C. 2010. Simulation Platform for the Evaluation of Robotic Swarm Algorithms, in Nishino, H. (ed), 2010 IEEE Region 10 Conference, Nov 21 2010, pp. 1583-1588. Fukuoka, Japan: IEEE.
    Source Title
    Proceedings of 2010 IEEE Region 10 Conference
    Source Conference
    2010 IEEE Region 10 Conference
    DOI
    10.1109/TENCON.2010.5686044
    ISBN
    9781424468881
    School
    Department of Electrical and Computer Engineering
    Remarks

    Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/5394
    Collection
    • Curtin Research Publications
    Abstract

    One major problem in the development of robotic swarms is the slow process of testing. Testing different algorithms or variations of a single one using physical robots requires reprogramming every robot in the swarm before every run. Hence, the speed at which a robotic swarm can be tested is highly dependent on the time taken to reprogram the entire swarm and the physical speed at which the swarm operates. This paper details the development of a computer-based simulation platform for rapid development and testing of swarm-intelligence algorithms in an effort to mitigate the current bottleneck imposed by testing. The simulator uses an object-oriented programming environment to facilitate the implementation and modification of swarm algorithms. Simulation of food foraging in an ant-hill scenario is used to demonstrate the effectiveness of the simulator.

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