DocumentCode :
161880
Title :
An image processing approach for determining the relative pose of unmanned underwater vehicles
Author :
Rzhanov, Yuri ; Eren, Firat ; Thein, May-Win ; Pe´eri, Shachak
Author_Institution :
Univ. of New Hampshire, Durham, NH, USA
fYear :
2014
fDate :
7-10 April 2014
Firstpage :
1
Lastpage :
4
Abstract :
The use of a light source as a beacon is advantageous for the guidance and control of Unmanned Underwater Vehicles (UUVs). This approach allows a follower UUV to determine its relative pose (position and orientation) using low-cost commercial off the shelf (COTS) hardware (e.g., metal halide light sources). In order to design an effective detector unit for the follower UUV and predict its performance, a simulator program has been developed. The program simulates a light field using hardware and environmental parameters describing the light source, water properties, the detector unit geometry and electronic sensitivity. The simulator allows examination of different 3D detector array shapes of varying sizes (physical dimensions and number of detectors). It is convenient to present simulator output as an image, where each pixel represents the intensity logged by a corresponding detector. These image outputs are evaluated for the development of control algorithms for UUVs. Currently control algorithms assume that the water column is uniform with a background noise of known origin. Considered control algorithms are able to provide guidance based on relative intensity values, where the light field samples on the detector array resembles a Gaussian beam pattern. However, disturbances in the medium (e.g., sediment plume) may cause non-uniform distribution of the scatterers that distort the beam pattern. As a result, the control algorithms could misinterpret the acquired image and direct the follower UUV away from the guiding beam. The probability for such a situation increases with distance as the beam diverges. This paper suggests an alternative approach for the development of UUV control algorithms using calculations of various moments of the image (e.g., local Hessian estimations). This method allows the evaluation of the array performance with different array geometries and a varying number of detector elements.
Keywords :
Gaussian processes; image processing; remotely operated vehicles; robot vision; underwater vehicles; COTS; Gaussian beam pattern; Hessian estimations; UUV; array geometries; array performance with; background noise; detector elements; detector unit geometry; electronic sensitivity; environmental parameters; hardware parameters; image processing approach; light field samples; light source; low-cost commercial off the shelf; relative pose; unmanned underwater vehicles; Arrays; Detectors; Geometry; Light sources; Noise; Robustness; Underwater vehicles; detector design; optical communication; simulation; unmanned underwater vehicle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
OCEANS 2014 - TAIPEI
Conference_Location :
Taipei
Print_ISBN :
978-1-4799-3645-8
Type :
conf
DOI :
10.1109/OCEANS-TAIPEI.2014.6964313
Filename :
6964313
Link To Document :
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