Abstract
This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno fuzzy model based on observation for nonlinear system is adopted to represent the process and measurement models of the vehicle-landmarks system. The complete system of the vehicle-landmarks model is decomposed into several linear models. Using the Kalman filter theory, each local model is filtered to find the local estimates. The linear combination of these local estimates gives the global estimate for the complete system. The simulation results prove that the new approach results in more anticipated performances, though nonlinearity is directly involved in the Kalman filter equations, compared to the conventional approach.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2007 3rd International Conference on Information and Automation for Sustainability, ICIAFS |
| Pages | 70-75 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2007 |
| Externally published | Yes |
| Event | 2007 3rd International Conference on Information and Automation for Sustainability, ICIAFS - Melbourne, Australia Duration: Dec 4 2007 → Dec 6 2007 |
Other
| Other | 2007 3rd International Conference on Information and Automation for Sustainability, ICIAFS |
|---|---|
| Country | Australia |
| City | Melbourne |
| Period | 12/4/07 → 12/6/07 |
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ASJC Scopus subject areas
- Information Systems
- Electrical and Electronic Engineering
Cite this
A fuzzy logic based approach to the SLAM problem using pseudolinear models with two sensors data association. / Pathiranage, Chandima Dedduwa; Udawatta, Lanka; Watanabe, Keigo; Izumi, Kiyotaka.
Proceedings of the 2007 3rd International Conference on Information and Automation for Sustainability, ICIAFS. 2007. p. 70-75 4544782.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A fuzzy logic based approach to the SLAM problem using pseudolinear models with two sensors data association
AU - Pathiranage, Chandima Dedduwa
AU - Udawatta, Lanka
AU - Watanabe, Keigo
AU - Izumi, Kiyotaka
PY - 2007
Y1 - 2007
N2 - This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno fuzzy model based on observation for nonlinear system is adopted to represent the process and measurement models of the vehicle-landmarks system. The complete system of the vehicle-landmarks model is decomposed into several linear models. Using the Kalman filter theory, each local model is filtered to find the local estimates. The linear combination of these local estimates gives the global estimate for the complete system. The simulation results prove that the new approach results in more anticipated performances, though nonlinearity is directly involved in the Kalman filter equations, compared to the conventional approach.
AB - This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno fuzzy model based on observation for nonlinear system is adopted to represent the process and measurement models of the vehicle-landmarks system. The complete system of the vehicle-landmarks model is decomposed into several linear models. Using the Kalman filter theory, each local model is filtered to find the local estimates. The linear combination of these local estimates gives the global estimate for the complete system. The simulation results prove that the new approach results in more anticipated performances, though nonlinearity is directly involved in the Kalman filter equations, compared to the conventional approach.
UR - http://www.scopus.com/inward/record.url?scp=51149101221&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51149101221&partnerID=8YFLogxK
U2 - 10.1109/ICIAFS.2007.4544782
DO - 10.1109/ICIAFS.2007.4544782
M3 - Conference contribution
AN - SCOPUS:51149101221
SN - 9781424419005
SP - 70
EP - 75
BT - Proceedings of the 2007 3rd International Conference on Information and Automation for Sustainability, ICIAFS
ER -