A novel hypothesis splitting method implementation for multi-hypothesis filters

Enis Bayramoglu, Ole Ravn, Nils Axel Andersen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The paper presents a multi-hypothesis filter library featuring a novel method for splitting Gaussians into ones with smaller variances. The library is written in C++ for high performance and the source code is open and free1. The multi-hypothesis filters commonly approximate the distribution transformations better, if the covariances of the individual hypotheses are sufficiently small. We propose a look-up table based method to calculate a set of Gaussian hypotheses approximating a wider Gaussian in order to improve the filter approximation. Python bindings for the library are also provided for fast prototyping.
Original languageEnglish
Title of host publicationProceedings of the 2013 10th IEEE International Conference on Control and Automation
PublisherIEEE
Publication date2013
Pages574-579
ISBN (Print)9781467347075
DOIs
Publication statusPublished - 2013
Event2013 10th IEEE International Conference on Control and Automation (ICCA) - Hangzhou, China
Duration: 12 Jun 201314 Jun 2013

Conference

Conference2013 10th IEEE International Conference on Control and Automation (ICCA)
CountryChina
CityHangzhou
Period12/06/201314/06/2013

Keywords

  • Approximation theory
  • C++ language
  • Filtering theory
  • Gaussian distribution
  • Mobile robots
  • Public domain software
  • Software libraries
  • Table lookup

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