T-S fuzzy model adopted SLAM algorithm with linear programming based data association for mobile robots

Chandima Dedduwa Pathiranage, Keigo Watanabe, Kiyotaka Izumi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper describes a Takagi-Sugeno (T-S) fuzzy model adopted solution to the simultaneous localization and mapping (SLAM) problem with two-sensor data association (TSDA) method. Nonlinear process model and observation model are formulated as pseudolinear models and rewritten with a composite model whose local models are linear according to T-S fuzzy model. Combination of these local state estimates results in global state estimate. This paper introduces an extended TSDA (ETSDA) method for the SLAM problem in mobile robot navigation based on an interior point linear programming (LP) approach. Simulation results are given to demonstrate that the ETSDA method has low computational complexity and it is more accurate than the existing single-scan joint probabilistic data association method. The above system is implemented and simulated with Matlab to claim that the proposed method yet finds a better solution to the SLAM problem than the conventional extended Kalman filter - SLAM algorithm.

Original languageEnglish
Pages (from-to)345-364
Number of pages20
JournalSoft Computing
Volume14
Issue number4
DOIs
Publication statusPublished - 2010
Externally publishedYes

Fingerprint

Data Association
Takagi-Sugeno Fuzzy Model
Simultaneous Localization and Mapping
Mobile Robot
Linear programming
Mobile robots
Sensor
Robot Navigation
Nonlinear Process
Interior Point
Model
Estimate
Kalman Filter
Low Complexity
Process Model
MATLAB
Nonlinear Model
Computational Complexity
Sensors
Extended Kalman filters

Keywords

  • Data association
  • Fuzzy Kalman filtering
  • Pseudolinear model
  • Simultaneous localization and mapping
  • T-S fuzzy model

ASJC Scopus subject areas

  • Software
  • Geometry and Topology
  • Theoretical Computer Science

Cite this

T-S fuzzy model adopted SLAM algorithm with linear programming based data association for mobile robots. / Pathiranage, Chandima Dedduwa; Watanabe, Keigo; Izumi, Kiyotaka.

In: Soft Computing, Vol. 14, No. 4, 2010, p. 345-364.

Research output: Contribution to journalArticle

Pathiranage, Chandima Dedduwa ; Watanabe, Keigo ; Izumi, Kiyotaka. / T-S fuzzy model adopted SLAM algorithm with linear programming based data association for mobile robots. In: Soft Computing. 2010 ; Vol. 14, No. 4. pp. 345-364.
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