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Swarm Optimization Algorithm for Road Bypass Extrapolation

  • Michael A. RowlandEmail author
  • Glenn M. Suir
  • Michael L. Mayo
  • Austin Davis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11844)

Abstract

Ant Colony Optimization (ACO) algorithms work by leveraging a population of agents that communicate through interaction with deposited “pheromone,” and have been applied in various configurations to the long-standing problem of identifying trafficable terrain from aerial imagery. While these approaches have proven successful in highlighting paved roads in urban, highly-developed sites, they tend to fail in peri-urban and rural locations due to the lower frequency of unnatural features. In this work, we describe a workflow that uses site-specific, near-infrared and first-return LIDAR data to predict the “accessible space” of an image–i.e., the more open regions with shallow elevation gradient that may be readily traversible by both mounted (e.g., all-terrain vehicles) and dismounted forces. Collectively, these regions are supplied as input to an ACO algorithm, modified so that the agents perform a random walk weighted by local elevation change, which allows for a more comprehensive exploration of increasingly featureless imaged terrain. Performance of this workflow is evaluated using two study sites in the continental United States: the Muscatatuck Urban Training Center in rural Indiana, and Camp Shelby in Mississippi. Comparison of results with ground-truth datasets show a high degree of success in predicting areas trafficable by a wide variety of mobile units.

Keywords

Image analysis Swarm optimization Trafficability 

Notes

Acknowledgments

Opinions, interpretations, conclusions, and recommendations are those of the author(s) and are not necessarily endorsed by the U.S. Army.

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Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019

Authors and Affiliations

  • Michael A. Rowland
    • 1
    Email author
  • Glenn M. Suir
    • 1
  • Michael L. Mayo
    • 1
  • Austin Davis
    • 1
  1. 1.U.S. Army Engineer Research and Development CenterVicksburgUSA

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