Robot Localization under Dynamic Uncertainty

  • S. Bartkevičius Kaunas University of Technology
  • R. Urniežius Kaunas University of Technology
  • S. Žebrauskas Kaunas University of Technology

Abstract

Maximum relative entropy approach for determination of robot localization principles is developed and confirmed through simulation experiments. The approach updates probability posterior using simultaneous updating of model combination and data. Model combination is performed using simultaneous validation and estimation of observed data. This approach is not restricted to robot localization tasks, but it can be used in a wide range of fields, including econometrics, physics and other technological sciences. This approach can be used in high volume real time systems, including signal analysis. Ill. 2, bibl. 5 (in English; summaries in English, Russian and Lithuanian).

Published
2015-02-20
Section
T 125 AUTOMATION, ROBOTICS