News Stories

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  • September

    Using virtual solutions for robotic testing during the COVID-19 pandemic

    Researchers at the U.S. Army Engineer Research and Development Center (ERDC) are accustomed to finding unique and innovative approaches to solving today’s most challenging engineering problems. The current COVID-19 environment presented new obstacles for the Sensor Integration Branch (SIB) in the ERDC’s Information Technology Laboratory (ITL) and Environmental Processes Branch (CNE) in the ERDC’s Construction Engineering Research Laboratory, prompting the robotics group to capitalize on simulation software capabilities to meet mission requirements.
  • ERDC researchers developing low-cost, rapid watershed assessment

    Researchers from the U.S. Army Engineer Research and Development Center (ERDC) have partnered with the U.S. Army Corps of Engineers (USACE) Vicksburg District to develop and test a low-cost, rapid watershed assessment using remote sensing technology to evaluate problems associated with watershed instability including erosion, sedimentation, flooding and environmental degradation.
  • March

    U.S. Army Engineer Research and Development Center assists in mudslide assessment

    A team of researchers from the U.S. Army Engineer Research and Development Center assisted the Vicksburg National Military Park in assessing landslides and erosion on the grounds.

News Releases

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  • PUBLICATION NOTIFICATION: Coincidence Processing of Photon-Sensitive Mapping Lidar Data

    Link: http://dx.doi.org/10.21079/11681/35599  Report Number: ERDC/GRL TR-20-1 Title: Coincidence Processing of Photon-Sensitive Mapping Lidar Data By Christian Marchant, Ryan Kirkpatrick, and David Ober Approved for Public Release; Distribution is Unlimited February 2020 Abstract: Photon-sensitive mapping lidar systems are able to image at greater collection area rates and ranges than linear-mode systems. However, these systems also experience greater noise levels due to shot noise, image blur, and dark current, which must be filtered out before the imagery can be exploited. Described in this report is a synthetic test data set of imagery from a notional airborne Geiger-mode lidar. Also described is the Bridge Sign algorithm, which uses a least-squares technique for noise filtering. The algorithm’s performance was validated using synthetic test imagery of both a toy scene and of a realistic scene, which were generated using the parameters of a notional airborne Geiger-mode system. Analysis of the results shows the technique effectively removes noise and preserves fine details with good fidelity. 30 pages / 1.568 Mb

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