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    An underwater electrosensory membrane bio-inspired by weakly electric fish

    Access Status
    Fulltext not available
    Authors
    Wang, Ke
    Cui, Lei
    Do, Khac Duc
    Date
    2016
    Type
    Conference Paper
    
    Metadata
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    Citation
    Wang, K. and Cui, L. and Do, K.D. 2016. An underwater electrosensory membrane bio-inspired by weakly electric fish, IEEE International Conference on Intelligent Robots and Systems, pp. 4951-4956.
    Source Title
    IEEE International Conference on Intelligent Robots and Systems
    DOI
    10.1109/IROS.2016.7759727
    ISBN
    9781509037629
    School
    Department of Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/51413
    Collection
    • Curtin Research Publications
    Abstract

    Artificial sensory system is promising to navigate in cluttered and turbid underwater environment by achieving similar functions of biological electrosense of weakly electric fish. In this paper we designed an electrosensory membrane that can operate in a full 3-dimensional mode. Algorithms on the object localization were also designed and tested based on numerical methods of electric field forward simulation. We combined the statistic learning method by training a multilayer neural network and a probabilistic approach by applying a constrained unscented Kalman filter (CUKF). This exploits the merits of fast estimation and precise signal marching process. Experimental results showed that the detection and localization with the reported sensor were quick and accurate, with errors of around 10 mm using one-step neural network mapping and about 5 mm in close-range using CUKF. This work demonstrated the effectiveness of proposed electrosensory membrane and algorithms.

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