T-S Fuzzy Model Adopted SLAM Algorithm with Linear Programming Based Data Association for Mobile Robots

被引：2
作者：
Watanabe, Keigo [1 ]
Pathiranage, Chandima Dedduwa [1 ]
Izumi, Kiyoaka [1 ]
机构：
[1] Saga Univ, Dept Adv Syst Control Engn, Grad Sch Sci & Engn, Saga 8408502, Japan
来源：
ISIE: 2009 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS | 2009年
关键词：
SIMULTANEOUS LOCALIZATION; NAVIGATION;
D O I：
10.1109/ISIE.2009.5217924
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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. Fuzzy Kalman filtering of the SLAM problem (FKF-SLAM) is used in this paper together with newly proposed data association algorithm. An extended TSDA (ETSDA) method is introduced 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 (JPDA) method.
引用
收藏
页码：244 / 249
页数：6
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