Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization
Simultaneous Localization and Mapping (SLAM) has become a foundational concept in robotics navigation in which enabling autonomous systems to build maps of unknown environments while estimating their own position. This article aims to provide a comprehensive review of SLAM concept in the context of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
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National Research and Innovation Agency (BRIN)
2025
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| Online Access: | https://umpir.ump.edu.my/id/eprint/45196/ |
| _version_ | 1848827350842605568 |
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| author | Muhammad Haniff, Gusrial Nur Aqilah, Othman Hamzah, Ahmad Mohd Hasnun Ariff, Hassan |
| author_facet | Muhammad Haniff, Gusrial Nur Aqilah, Othman Hamzah, Ahmad Mohd Hasnun Ariff, Hassan |
| author_sort | Muhammad Haniff, Gusrial |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Simultaneous Localization and Mapping (SLAM) has become a foundational concept in robotics navigation in which enabling autonomous systems to build maps of unknown environments while estimating their own position. This article aims to provide a comprehensive review of SLAM concept in the context of mobile robotics navigation by focusing on theoretical principles, estimation problem, algorithm involved and related application. The existing literature is systematically analyzed and classified based on three main perspectives of navigation which are localization, mapping and path planning. Particular attention is given to Kalman filters and its variants in SLAM-based systems along with crucial consideration of the linearization and covariance initialization. This article identifies strengths and limitations of current SLAM approaches. Therefore, this article concludes by outlining research gaps and recommending directions for future exploration, with the intention of serving as a foundation for continued innovation in SLAM-based robotic navigation systems. |
| first_indexed | 2025-11-15T03:59:19Z |
| format | Article |
| id | ump-45196 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:59:19Z |
| publishDate | 2025 |
| publisher | National Research and Innovation Agency (BRIN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-451962025-08-01T01:04:36Z https://umpir.ump.edu.my/id/eprint/45196/ Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization Muhammad Haniff, Gusrial Nur Aqilah, Othman Hamzah, Ahmad Mohd Hasnun Ariff, Hassan TK Electrical engineering. Electronics Nuclear engineering Simultaneous Localization and Mapping (SLAM) has become a foundational concept in robotics navigation in which enabling autonomous systems to build maps of unknown environments while estimating their own position. This article aims to provide a comprehensive review of SLAM concept in the context of mobile robotics navigation by focusing on theoretical principles, estimation problem, algorithm involved and related application. The existing literature is systematically analyzed and classified based on three main perspectives of navigation which are localization, mapping and path planning. Particular attention is given to Kalman filters and its variants in SLAM-based systems along with crucial consideration of the linearization and covariance initialization. This article identifies strengths and limitations of current SLAM approaches. Therefore, this article concludes by outlining research gaps and recommending directions for future exploration, with the intention of serving as a foundation for continued innovation in SLAM-based robotic navigation systems. National Research and Innovation Agency (BRIN) 2025 Article PeerReviewed pdf en https://umpir.ump.edu.my/id/eprint/45196/1/Review%20of%20Kalman%20filter%20variants%20for%20SLAM%20in%20mobile%20robotics.pdf pdf en cc_by_nc_sa_4 https://umpir.ump.edu.my/id/eprint/45196/7/Review%20of%20Kalman%20filter%20variants%20for%20SLAM%20in%20mobile%20robotics.pdf Muhammad Haniff, Gusrial and Nur Aqilah, Othman and Hamzah, Ahmad and Mohd Hasnun Ariff, Hassan (2025) Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization. Journal of Mechatronics, Electrical Power, and Vehicular Technology, 16 (1). pp. 69-83. ISSN 2087-3379. (Published) https://doi.org/10.55981/j.mev.2025.1096 https://doi.org/10.55981/j.mev.2025.1096 https://doi.org/10.55981/j.mev.2025.1096 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Muhammad Haniff, Gusrial Nur Aqilah, Othman Hamzah, Ahmad Mohd Hasnun Ariff, Hassan Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title | Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title_full | Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title_fullStr | Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title_full_unstemmed | Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title_short | Review of Kalman filter variants for SLAM in mobile robotics with linearization and covariance initialization |
| title_sort | review of kalman filter variants for slam in mobile robotics with linearization and covariance initialization |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | https://umpir.ump.edu.my/id/eprint/45196/ https://umpir.ump.edu.my/id/eprint/45196/ https://umpir.ump.edu.my/id/eprint/45196/ |