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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Evidential logical sensing using multiple sonars for the identification of target primitives in a mobile robot's environment

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      Author(s)
      Ayrulu, Birsel
      Barshan, Billur
      Erkmen, İ.
      Erkmen, A.
      Date
      1996
      Source Title
      Proceedings of the 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems
      Publisher
      IEEE
      Pages
      365 - 372
      Language
      English
      Type
      Conference Paper
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      Abstract
      Physical models are used to model reflections from target primitives commonly encountered in mobile robot applications. These targets are differentiated by employing a multi-transducer pulse/echo system which relies on both amplitude and time-of-flight (TOF) data in the feature fusion process, allowing more robust differentiation. Target features are generated as being evidentially tied to degrees of belief which are subsequently fused for multiple logical sonars at different geographical sites. This evidential approach helps to overcome the vulnerability of echo amplitude to noise and enables the modeling of non-parametric uncertainty. Feature data from multiple logical sensors are fused with Dempster-Shafer rule of combination to improve the performance of classification by reducing perception uncertainty. Using three sensing nodes, improvement in differentiation is between 20-40% without false decision, at the cost of additional computation. Simulation results are verified by experiments with a real sonar system. This evidential approach helps to overcome the vulnerability of the echo amplitude to noise and enables the modeling of non-parametric uncertainty in real time.
      Keywords
      Computer simulation
      Feature extraction
      Parameter estimation
      Robustness (control systems)
      Sensor data fusion
      Sonar
      System stability
      Evidential logical sensing
      Time of flight data
      Mobile robots
      Permalink
      http://hdl.handle.net/11693/27733
      Published Version (Please cite this version)
      https://doi.org/10.1109/MFI.1996.572202
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      • Department of Electrical and Electronics Engineering 3868
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