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Terrain-Aided Localization Using Feature-Based Particle Filtering

[+] Author Affiliations
Sneha Kadetotad, Pramod K. Vemulapalli, Sean N. Brennan, Constantino Lagoa

Pennsylvania State University, University Park, PA

Paper No. DSCC2011-6025, pp. 725-731; 7 pages
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 2
  • Arlington, Virginia, USA, October 31–November 2, 2011
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5476-1
  • Copyright © 2011 by ASME


The localization of vehicles on roadways without the use of a GPS has been of great interest in recent years and a number of solutions have been proposed for the same. The localization of vehicles has traditionally been divided by their solution approaches into two different categories: global localization which uses feature-vector matching, and local tracking which has been dealt by using techniques like Particle Filtering or Kalman Filtering. This paper proposes a unifying approach that combines the feature-based robustness of global search with the local tracking capabilities of a particle filter. Using feature vectors produced from pitch measurements from Interstate I-80 and US Route 220 in Pennsylvania, this work demonstrates wide area localization of a vehicle with the computational efficiency of local tracking.

Copyright © 2011 by ASME



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