A solution to partial observability in extended Kalman Filter mobile robot navigation
Partial observability in EKF based mobile robot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. By only considering certain landmarks in an environment, the computational cost in mobile robot can be reduced but with an increase of uncertainties to t...
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| Language: | en |
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Universitas Ahmad Dahlan
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/21076/1/A%20solution%20to%20partial%20observability%20in%20extended%20kalman%20filter%20mobile%20robot%20navigation.pdf http://umpir.ump.edu.my/id/eprint/21076/ http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/9025/pdf_588 |
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| author | Hamzah, Ahmad Nur Aqilah, Othman Mohd Syakirin, Ramli |
| author_facet | Hamzah, Ahmad Nur Aqilah, Othman Mohd Syakirin, Ramli |
| author_sort | Hamzah, Ahmad |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Partial observability in EKF based mobile robot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. By only considering certain landmarks in an environment, the computational cost in mobile robot can be reduced but with an increase of uncertainties to the system. This is known as suboptimal condition of the system. Fuzzy Logic technique is proposed to ensure that the estimation achieved desired performance even though some of the landmarks were excluded for references. The Fuzzy Logic is applied to the measurement innovation of Kalman Filter to correct the positions of both mobile robot and any observed landmarks during observations. The simulation results shown that the proposed method is capable to secure reliable estimation results even a number of landmarks being excluded from Kalman Filter update process in both Gaussian and non-Gaussian noise conditions. |
| format | Article |
| id | my.ump.umpir.21076 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2018 |
| publisher | Universitas Ahmad Dahlan |
| record_format | eprints |
| spelling | my.ump.umpir.210762018-08-28T09:01:05Z http://umpir.ump.edu.my/id/eprint/21076/ A solution to partial observability in extended Kalman Filter mobile robot navigation Hamzah, Ahmad Nur Aqilah, Othman Mohd Syakirin, Ramli TK Electrical engineering. Electronics Nuclear engineering Partial observability in EKF based mobile robot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. By only considering certain landmarks in an environment, the computational cost in mobile robot can be reduced but with an increase of uncertainties to the system. This is known as suboptimal condition of the system. Fuzzy Logic technique is proposed to ensure that the estimation achieved desired performance even though some of the landmarks were excluded for references. The Fuzzy Logic is applied to the measurement innovation of Kalman Filter to correct the positions of both mobile robot and any observed landmarks during observations. The simulation results shown that the proposed method is capable to secure reliable estimation results even a number of landmarks being excluded from Kalman Filter update process in both Gaussian and non-Gaussian noise conditions. Universitas Ahmad Dahlan 2018-02 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/21076/1/A%20solution%20to%20partial%20observability%20in%20extended%20kalman%20filter%20mobile%20robot%20navigation.pdf Hamzah, Ahmad and Nur Aqilah, Othman and Mohd Syakirin, Ramli (2018) A solution to partial observability in extended Kalman Filter mobile robot navigation. Telkomnika (Telecommunication Computing Electronics and Control), 16 (1). pp. 134-141. ISSN 1693-6930. (Published) http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/9025/pdf_588 10.12928/TELKOMNIKA.v16i1.9025 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Hamzah, Ahmad Nur Aqilah, Othman Mohd Syakirin, Ramli A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title | A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title_full | A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title_fullStr | A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title_full_unstemmed | A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title_short | A solution to partial observability in extended Kalman Filter mobile robot navigation |
| title_sort | solution to partial observability in extended kalman filter mobile robot navigation |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/21076/1/A%20solution%20to%20partial%20observability%20in%20extended%20kalman%20filter%20mobile%20robot%20navigation.pdf http://umpir.ump.edu.my/id/eprint/21076/ http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/9025/pdf_588 |
| url_provider | http://umpir.ump.edu.my/ |