Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM
Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landmarks in Simultaneous Localization and Mapping (SLAM). Nonetheless, there are some disadvantages of using EKF, namely the requirement of Gaussian distribution for the state and noises, as well as the f...
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| Format: | Article |
| Language: | English English |
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Hindawi Publishing Corporation
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/7109/1/fkee-2014-hamzah-inpress.pdf http://umpir.ump.edu.my/id/eprint/7109/4/fkee-2015-aqilah-Sufficient%20Condition%20for%20Estimation.pdf |
| _version_ | 1796990214893207552 |
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| author | Hamzah, Ahmad Nur Aqilah, Othman Namerikawa, Toru |
| author_facet | Hamzah, Ahmad Nur Aqilah, Othman Namerikawa, Toru |
| author_sort | Hamzah, Ahmad |
| collection | UMP |
| description | Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landmarks in Simultaneous Localization and Mapping (SLAM). Nonetheless, there are some disadvantages of using EKF, namely the requirement of Gaussian distribution for the state and noises, as well as the fact that it requires the smallest possible initial state covariance. This has led researchers to find alternative ways to mitigate the aforementioned shortcomings. Therefore, this study is conducted to propose an alternative technique by implementing H� filter in SLAM instead of EKF. In implementing H� filter in SLAM, the parameters of the filter especially
� needs to be properly defined to prevent finite escape time problem. Hence, this study proposes a sufficient condition for the estimation
purposes. Two distinct cases of initial state covariance are analysed considering an indoor environment to ensure the best solution for SLAM problem exists along with considerations of process and measurement noises statistical behaviour. If the prescribed conditions are not satisfied, then the estimation would exhibit unbounded uncertainties and consequently results in erroneous inference about the robot and landmarks estimation. The simulation results have shown the reliability and consistency as suggested by the theoretical analysis and our previous findings. |
| first_indexed | 2024-03-06T11:48:16Z |
| format | Article |
| id | UMPir7109 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T11:48:16Z |
| publishDate | 2015 |
| publisher | Hindawi Publishing Corporation |
| record_format | dspace |
| spelling | UMPir71092018-02-05T06:50:49Z http://umpir.ump.edu.my/id/eprint/7109/ Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM Hamzah, Ahmad Nur Aqilah, Othman Namerikawa, Toru TK Electrical engineering. Electronics Nuclear engineering Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landmarks in Simultaneous Localization and Mapping (SLAM). Nonetheless, there are some disadvantages of using EKF, namely the requirement of Gaussian distribution for the state and noises, as well as the fact that it requires the smallest possible initial state covariance. This has led researchers to find alternative ways to mitigate the aforementioned shortcomings. Therefore, this study is conducted to propose an alternative technique by implementing HâÂ�Â� filter in SLAM instead of EKF. In implementing HâÂ�Â� filter in SLAM, the parameters of the filter especially ïÂ�§ needs to be properly defined to prevent finite escape time problem. Hence, this study proposes a sufficient condition for the estimation purposes. Two distinct cases of initial state covariance are analysed considering an indoor environment to ensure the best solution for SLAM problem exists along with considerations of process and measurement noises statistical behaviour. If the prescribed conditions are not satisfied, then the estimation would exhibit unbounded uncertainties and consequently results in erroneous inference about the robot and landmarks estimation. The simulation results have shown the reliability and consistency as suggested by the theoretical analysis and our previous findings. Hindawi Publishing Corporation 2015 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7109/1/fkee-2014-hamzah-inpress.pdf application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/7109/4/fkee-2015-aqilah-Sufficient%20Condition%20for%20Estimation.pdf Hamzah, Ahmad and Nur Aqilah, Othman and Namerikawa, Toru (2015) Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM. Mathematical Problems in Engineering, 2015. pp. 1-14. ISSN 1024-123X (print); 1563-5147 (online). (Published) http://dx.doi.org/10.1155/2015/238131 DOI: 10.1155/2015/238131 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Hamzah, Ahmad Nur Aqilah, Othman Namerikawa, Toru Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title | Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title_full | Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title_fullStr | Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title_full_unstemmed | Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title_short | Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM |
| title_sort | sufficient condition for estimation in designing h∞ filter based slam |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/7109/1/fkee-2014-hamzah-inpress.pdf http://umpir.ump.edu.my/id/eprint/7109/4/fkee-2015-aqilah-Sufficient%20Condition%20for%20Estimation.pdf |
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