Simultaneous localization and mapping: A pseudolinear kalman filter (plkf) approach

Chandima Dedduwa Pathiranage, Keigo Watanabe, Buddhika Jayasekara, Kiyotaka Izumi

研究成果

6 被引用数 (Scopus)

抄録

This paper describes an improved solution to the simultaneous localization and mapping (SLAM) problem based on pseudolinear models. Accurate estimation of vehicle and landmark states is one of the key issues for successful mobile robot navigation if the configuration of the environment and initial robot location are unknown. A state estimator which can be designed to use the nonlinearity as it is coming from the original model has always been invaluable in which high accuracy is expected. Thus to accomplish the above highlighted point, pseudolinear model based Kalman filter (PLKF) state estimator is introduced. Evolution of vehicle motion is modeled using vehicle frame translation derived from successive dead reckoned poses as a control input. A pseudolinear process model is proposed to improve the accuracy and the faster convergence of state estimation. The general sensor model is presented in a pseudolinear form to preserve the nonlinearity in the observation model. The PLKF-based SLAM algorithm is simulated using Matlab for vehicle-landmarks system and results show that the proposed approach performs much accurately compared to the well known EKF-SLAM algorithm.

本文言語English
ホスト出版物のタイトルProceedings of the 2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008
ページ61-66
ページ数6
DOI
出版ステータスPublished - 2008
外部発表はい
イベント2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008 - Colombo
継続期間: 12月 12 200812月 14 2008

出版物シリーズ

名前Proceedings of the 2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008

Other

Other2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008
国/地域Sri Lanka
CityColombo
Period12/12/0812/14/08

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用
  • 制御およびシステム工学

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