Accelerating Point Set Registration for Automated Aerial Refueling

Abstract

The goal of AAR is to control the tanker boom to safely refuel a receiving aircraft with no input or aid from the boom operator. To achieve this, the pose of the receiver relative to the tanker must be known. Point set registration is a fundamental issue used to estimate the relative pose of an object in an environment. However, it's likely a computational bottleneck of a vision processing pipeline. In addition, the matching of each sensed point with a closest truth point, nearest neighbor matching, is the most costly portion of the point set registration process. For this reason, this research focuses on speeding up the ICP algorithm and nearest neighbor algorithms. This research lays out novel nearest neighbor matching algorithms based on the Delaunay triangulation with a reduced cost compared to conventional nearest neighbor matching algorithms. The ICP algorithm is transformed into a massively parallel algorithm and mapped onto a vector processor to realize a speedup of approximately 2 orders of magnitude. Lastly, this thesis presents algorithmic and runtime analysis with augmented, virtual, and real experiments.

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Document Details

Document Type
Technical Report
Publication Date
Mar 19, 2021
Accession Number
AD1134593

Entities

People

  • Ryan M. Raettig

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Autonomous Systems
  • Central Processing Units
  • Computational Science
  • Computer Programming
  • Computer Vision
  • Computers
  • Data Mining
  • Engineering
  • Graphics Processing Unit
  • Image Processing
  • Information Science
  • Literature Surveys
  • Machine Learning
  • Pattern Recognition
  • Point Clouds
  • Refueling
  • Refueling In Flight
  • Trees (Data Structures)

Readers

  • Aerospace logistics and air mobility.
  • Computer Vision.
  • Parallel and Distributed Computing.