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Title:Tactile tomographic imaging using robotic whiskers
Author(s):Tuna, Cagdas
Director of Research:Jones, Douglas L.
Doctoral Committee Chair(s):Jones, Douglas L.
Doctoral Committee Member(s):Hartmann, Mitra; Kamalabadi, Farzad; O'Brien, William D.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Robotic Whiskers
Bio-inspired Signal Processing
Tactile Sensing
Shape Recognition
Flow imaging
Inverse problem
Image Reconstruction
Abstract:Animals such as rats and seals sense through movement by oscillating their whiskers back and forth to extract environmental information including nearby object features and fluid-flow characteristics. However, current array sensory systems do not fully utilize tactile sensing strategies extensively used by these animals. This dissertation focuses on developing advanced bio-inspired signal processing algorithms for the reconstruction of surroundings with arrays of vibrissal sensors. Inspired by the oscillatory motions of the rat’s whiskers, we introduce a new tactile tomographic imaging model using robotic metal whiskers to extract object features including size, shape and location, and map out the cross-sectional fluid-flow characteristics via tomographic imaging. Comparing the whisker position at the very initial object contact to a ray path in X-ray tomography, we show that the problem of object shape recognition with robotic whiskers can be expressed as a 2-D tactile tomographic imaging procedure by using only the whisker base position and the angle at the whisker base during the very initial contact recorded at different locations around the object. At high Reynolds numbers, the drag force on a whisker segment is proportional to the relative velocity squared and hence, whether the flow is laminar or turbulent, we propose that it is possible to map out the 2-D cross-sectional mean fluid-flow velocity field using the moment measurements collected by a robotic whisker array from different directions for tomographic reconstruction. We also present a linear state-space formulation for the tactile dynamic tomographic fluid-flow imaging for the sequential estimation of the fluid-flow characteristics in a dynamically changing environment. The experimental results strongly demonstrate that this new tactile sensing technology developed in this dissertation may find a potential future use in various robotic applications including object feature extraction, object tracking, underwater navigation, high-resolution fluid-flow imaging, source localization and environmental mapping.
Issue Date:2014-05-30
Rights Information:Copyright 2014 Cagdas Tuna
Date Available in IDEALS:2014-05-30
Date Deposited:2014-05

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