Cloud-based map alignment strategies for multi-robot FastSLAM 2.0
The cooperative simultaneous localization and mapping problem has acquired growing attention over the years. Even though mapping of very large environments is theoretically quicker than a single robot simultaneous localization and mapping, it has several additional challenges such as the map alignme...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2019-03-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719829329 |
| _version_ | 1797719541307932672 |
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| author | Shimaa S Ali Abdallah Hammad Adly S Tag Eldien |
| author_facet | Shimaa S Ali Abdallah Hammad Adly S Tag Eldien |
| author_sort | Shimaa S Ali |
| collection | DOAJ |
| description | The cooperative simultaneous localization and mapping problem has acquired growing attention over the years. Even though mapping of very large environments is theoretically quicker than a single robot simultaneous localization and mapping, it has several additional challenges such as the map alignment and the merging processes, network latency, administering various coordinate systems and assuring synchronized and updated data from all robots and also it demands massive computation. This article proposes an efficient architecture for cloud-based cooperative simultaneous localization and mapping to parallelize its complex steps via the multiprocessor (computing nodes) and free the robots from all of the computation efforts. Furthermore, this work improves the map alignment part using hybrid combination strategies, random sample consensus, and inter-robot observations to exploit fully their advantages. The results show that the proposed approach increases mapping performance with less response time. |
| first_indexed | 2024-03-12T09:06:19Z |
| format | Article |
| id | doaj.art-00ee040efa9649109f0df5539a5823b8 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T09:06:19Z |
| publishDate | 2019-03-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-00ee040efa9649109f0df5539a5823b82023-09-02T15:15:09ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772019-03-011510.1177/1550147719829329Cloud-based map alignment strategies for multi-robot FastSLAM 2.0Shimaa S AliAbdallah HammadAdly S Tag EldienThe cooperative simultaneous localization and mapping problem has acquired growing attention over the years. Even though mapping of very large environments is theoretically quicker than a single robot simultaneous localization and mapping, it has several additional challenges such as the map alignment and the merging processes, network latency, administering various coordinate systems and assuring synchronized and updated data from all robots and also it demands massive computation. This article proposes an efficient architecture for cloud-based cooperative simultaneous localization and mapping to parallelize its complex steps via the multiprocessor (computing nodes) and free the robots from all of the computation efforts. Furthermore, this work improves the map alignment part using hybrid combination strategies, random sample consensus, and inter-robot observations to exploit fully their advantages. The results show that the proposed approach increases mapping performance with less response time.https://doi.org/10.1177/1550147719829329 |
| spellingShingle | Shimaa S Ali Abdallah Hammad Adly S Tag Eldien Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 International Journal of Distributed Sensor Networks |
| title | Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 |
| title_full | Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 |
| title_fullStr | Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 |
| title_full_unstemmed | Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 |
| title_short | Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 |
| title_sort | cloud based map alignment strategies for multi robot fastslam 2 0 |
| url | https://doi.org/10.1177/1550147719829329 |
| work_keys_str_mv | AT shimaasali cloudbasedmapalignmentstrategiesformultirobotfastslam20 AT abdallahhammad cloudbasedmapalignmentstrategiesformultirobotfastslam20 AT adlystageldien cloudbasedmapalignmentstrategiesformultirobotfastslam20 |