| Development and application of distributed MEMS pressure sensor array for AUV object avoidance - :9721 | Sea Grant Publications
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Development and application of distributed MEMS pressure sensor array for AUV object avoidance
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  • Corporate Authors:
    Massachusetts Institute of Technology, Sea Grant College Program, ; United States, National Oceanic and Atmospheric Administration, ;
  • Description:
    A novel sensory system is being developed for AUVs to augment current sensory systems for navigation and operation in difficult environments. These environments are frequently cluttered and murky with substantial flow from currents or waves, frustrating sonar and vision systems while posing an increased risk to AUVs. In order to manage such situations, a better ability to locate and identify physical objects is needed. This gap could be filled by small low frequency pressure sensors distributed over the surface of the AUV in dense arrays. The pressure sensor array presented here consists of hundreds of MEMS pressure sensors with diameters near 1 mm spaced a few millimeters apart fabricated on etched silicon and Pyrex wafers; a fabrication process for producing the array is described. A strain-gauge pressure sensor is analyzed, fabricated, and tested. It satisfies specifications as required for object detection. The sensing element is a strain gauge mounted on a flexible diaphragm, which is a thin (20 [mu]m) layer of silicon attached at the edges to a square silicon cavity 2000 [mu]m wide on a side. A source voltage of 10 V produces a sensor with a sensitivity on the order of 1 [mu]V/Pa. Since the thermal noise voltage is near 0.7 [mu]V, the pressure resolution of the sensors is on the order of 1 Pa. In addition to a pressure sensor array capable of measuring the spatial pressure distribution, progress has also been made in estimating the shape of an arbitrary two dimensional physical object in a flow and in tracking vortices based solely on distributed pressure measurements. The shape estimation relies on a conformal mapping which orders shape parameters by their observability with range. Utilizing this model, a sequential maximum likelihood estimation technique is able to extract the contour of an object in steady flow. This procedure requires no a priori knowledge of the type of object. The result is an estimate of a completely arbitrary shape whose level of generality depends on the distance of the object.

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  • Funding:
    Funding: National Oceanic and Atmospheric Administration; grant number: NA06OAR4170019; project number: R/RT-2/RCM-17.;
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