An improved adaptive FastSLAM algorithm with time‐varying noise estimator

Karaçam S., Navruz T. S.

ASIAN JOURNAL OF CONTROL, cilt.26, sa.4, ss.2617-2627, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 4
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1002/asjc.2968
  • Dergi Adı: ASIAN JOURNAL OF CONTROL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, INSPEC, zbMATH
  • Sayfa Sayıları: ss.2617-2627
  • Anahtar Kelimeler: adaptive FastSLAM, FastSLAM, simultaneous localization and mapping, time-varying noise estimator
  • Gazi Üniversitesi Adresli: Evet

Özet

n this study, an adaptive FastSLAM (AFastSLAM) algorithm, which is obtainedby estimating the time-varying noise statistics and improving FastSLAMalgorithm, is proposed. This improvement was accomplished by using max-imum likelihood estimation and expectation maximization criterion and aone-step smoothing algorithm in importance sampling. In addition, innovationcovarianceestimation(ICE)methodwasusedtopreventlossofpositivedefinite-ness of the process and measurement noise covariance matrices. The proposedmethodwascomparedwithFastSLAMbycalculatingtherootmeansquareerror(RMSE) using different particle numbers at varying initial process and measure-ment noise values. Simulation studies have shown that AFastSLAM providesmuch more accurate, consistent, and successful estimates than FastSLAM forboth robot and landmark positions.