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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008
Pages61-66
Number of pages6
DOIs
Publication statusPublished - Dec 1 2008
Externally publishedYes
Event2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008 - Colombo, Sri Lanka
Duration: Dec 12 2008Dec 14 2008

Publication series

NameProceedings 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
CountrySri Lanka
CityColombo
Period12/12/0812/14/08

Keywords

  • Odometry measurement
  • Pseudolinear kalman filter
  • Pseudolinear model
  • Simultaneous localization and mapping

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

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  • Cite this

    Pathiranage, C. D., Watanabe, K., Jayasekara, B., & Izumi, K. (2008). Simultaneous localization and mapping: A pseudolinear kalman filter (plkf) approach. In Proceedings of the 2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008 (pp. 61-66). [4783921] (Proceedings of the 2008 4th International Conference on Information and Automation for Sustainability, ICIAFS 2008). https://doi.org/10.1109/ICIAFS.2008.4783921