An efficient, on-line terrain-covering algorithm is presented for a robot (AUV) moving in an unknown three-dimensional underwater environment. Such an algorithm is necessary for producing mosaicked images of the ocean floor. The basis of this three-dimensional motion planning algorithm is a new planar algorithm for nonsimply connected areas with boundaries of arbitrary shape. We show that this algorithm generalizes naturally to complex three-dimensional environments in which the terrain to be covered is projectively planar. This planar algorithm represents an improvement over previous algorithms because it results in a shorter path length for the robot and does not assume a polygonal environment. The path length of our algorithm is shown to be linear in the size of the area to be covered; the amount of memory required by the robot to implement the algorithm is linear in the size of the description of the boundary of the area. An example is provided that demonstrates the algorithm’s performance in a nonsimply connected, nonplanar environment.

A terrain-covering algorithm for an AUV

/pdf/backscattering-phenomena-on-range-gated-imaging-in-short-2sac37zo83.pdf

Backscattering phenomena on range-gated imaging in short-range turbid water media.

In order to improve underwater visibility, general considerations are planned in two stages. There is hardware upgrading followed by system optimization stage. For the former, we choose to improve the underwater visibility with advanced techniques: range gated imaging system, and the optimization in terms of image processing techniques. Four selected image enhancement technique has been tested, namely Contrast Stretching, CLAHE, Illumination-reflectance Model and Homomorphic Filtering. Quantitative image quality measures are used to evaluate the enhanced imaging techniques. Three image assessment techniques are used to quantify image quality of the imaging system in increased turbidity condition, namely Modified Fidelity (MF), Modified Strehl Ratio (MSR2), and Contrast-to-Noise Ratio (CNR). In the first stage, the quantitative measures have shown at least 40% improvement from non-gated to gated images in increased turbidity. Finally, the enhancement techniques further improve the gated images with limited noise amplification issues.

Quantitative image quality evaluations of enhanced images in turbid water medium

This paper describes the main scientific and technical aspects foreseen for the development of the project BE-2013 titled VENICE (Virtual ENvironment interface by sensory integration for Inspection and manipulation Control in multifunctional underwater vehicles), financed by the European Commission under the programme BRITE-Euram III, related to the role of the Department of Mathematics and Computer Science of the University of Udine. This project is devoted to the study and development of methodologies for optimising acoustical and optical sensors' functioning and integrating related data for the formation of an accurate virtual environment aimed at supporting navigation, inspection, and maintenance/repair tasks of multifunctional remotely operated underwater vehicles.

/pdf/integration-of-optical-and-acoustical-imaging-sensors-for-4p8ntlyfea.pdf

Integration of Optical and Acoustical Imaging Sensors for Underwater Applications

it. In fact, video tape is recorded by the video camera which is settled on the AUV. Using these video tapes, we In this paper, we make an attempt to predict the location can know cable's status, and know whether the cable is in of a cable in next frame according to some parameters dangerous. in current frame. At first, the initial condition is that Developing with examination about the Underwater the approximate location of cable must be given. From Optical Cable Network, there are a lot of video tapes are Hough Transformation, a high accumulated degree point taken by the AUV's video camera. A useful automatic in ~~~~h Space is gotten. Aftemar&, by inverse ~~~~h algorithms which can recognize cable and find whether IPransfonnation, using that point, the location is detected the cable is in dangerous is required. This Paper shows and then cable is pointed out from its original image. a study on how to recognize an underwater cable effecBased on the actual working conditions and perfor- tively by means of time sequence of limited parameter mance indices, as well as the location in current frame, using HOugh Transformation. the maximum mnge of degree within which the cable maybe occurred in next frame with high possibility is evaluated. firthemore, a narrower mnge of location in next frame 2 Normalized Distribution is confinned according to the speed of robot. It is this nar

/pdf/a-study-on-underwater-cable-automatic-recognition-using-h7zi6jor90.pdf

A Study on Underwater Cable Automatic Recognition using Hough Transformation

The authors compare the performance of a spatial domain and a spatial frequency domain control method used to assess image content information from charge coupled device (CCD) camera imagery. Sample underwater images were processed using the developed techniques and are used to illustrate comparative levels of control for different water qualities, object contrasts, and ranges. The implementation algorithm required to use these techniques to control an autonomous underwater vehicle's camera light level and range-to-target distance is also presented. >

http://ieeexplore.ieee.org/iel2/663/5876/00225209.pdf

L.A. Lieberman

Papers

Automatic camera control for AUVs: a comparison of image assessment methods