Parallelized Iterative Closest Point for Autonomous Aerial Refueling

  • Jace Robinson
  • Matt Piekenbrock
  • Lee Burchett
  • Scott Nykl
  • Brian Woolley
  • Andrew Terzuoli
Conference paper

DOI: 10.1007/978-3-319-50835-1_53

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10072)
Cite this paper as:
Robinson J., Piekenbrock M., Burchett L., Nykl S., Woolley B., Terzuoli A. (2016) Parallelized Iterative Closest Point for Autonomous Aerial Refueling. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science, vol 10072. Springer, Cham

Abstract

The Iterative Closest Point algorithm is a widely used approach to aligning the geometry between two 3 dimensional objects. The capability of aligning two geometries in real time on low-cost hardware will enable the creation of new applications in Computer Vision and Graphics. The execution time of many modern approaches are dominated by either the k nearest neighbor search (kNN) or the point alignment phase. This work presents an accelerated alignment variant which utilizes parallelization on a Graphics Processing Unit (GPU) of multiple kNN approaches augmented with a novel Delaunay Traversal to achieve real time estimates.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Jace Robinson
    • 1
  • Matt Piekenbrock
    • 1
  • Lee Burchett
    • 1
  • Scott Nykl
    • 1
  • Brian Woolley
    • 1
  • Andrew Terzuoli
    • 1
  1. 1.Air Force Institute of TechnologyWright-PattersonUSA

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