Constrained-covisibility marginalization for efficient on-board stereo SLAM
When targeting embedded applications such as on-board visual localization for small Unmanned Air Vehicles (UAV), available hardware generally becomes a limiting factor. For this reason, the usual strategy is to rely on pure motion integration and/or restricting the size of the map, i.e. performing v...
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_97815386_v_n_p_Nitsche |
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todo:paper_97815386_v_n_p_Nitsche2023-10-03T16:43:59Z Constrained-covisibility marginalization for efficient on-board stereo SLAM Nitsche, M.A. Castro, G.I. Pire, T. Fischer, T. De Cristoforis, P. Mobile robots Stereo image processing Unmanned aerial vehicles (UAV) Vision Computational costs Computational time Embedded application Embedded computers Monocular vision Parallelizations Unmanned air vehicles Visual localization Stereo vision When targeting embedded applications such as on-board visual localization for small Unmanned Air Vehicles (UAV), available hardware generally becomes a limiting factor. For this reason, the usual strategy is to rely on pure motion integration and/or restricting the size of the map, i.e. performing visual odometry. Moreover, if monocular vision is employed, due to the additional computational cost of stereo vision, this requires dealing with the problem of unknown scale. In this work we discuss how the cost of the tracking task can be reduced without limiting the size of the global map. To do so, the notion of covisibility is strongly used which allows choosing a fixed and optimal set of points to be tracked. Moreover, this work delves into the concept of parallel tracking and mapping and presents some finer parallelization opportunities. Finally, we show how these strategies improve the computational times of a stereo visual SLAM framework called S-PTAM running on-board an embedded computer, close to camera frame-rates and with negligible precision loss. © 2017 IEEE. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97815386_v_n_p_Nitsche |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Mobile robots Stereo image processing Unmanned aerial vehicles (UAV) Vision Computational costs Computational time Embedded application Embedded computers Monocular vision Parallelizations Unmanned air vehicles Visual localization Stereo vision |
| spellingShingle |
Mobile robots Stereo image processing Unmanned aerial vehicles (UAV) Vision Computational costs Computational time Embedded application Embedded computers Monocular vision Parallelizations Unmanned air vehicles Visual localization Stereo vision Nitsche, M.A. Castro, G.I. Pire, T. Fischer, T. De Cristoforis, P. Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| topic_facet |
Mobile robots Stereo image processing Unmanned aerial vehicles (UAV) Vision Computational costs Computational time Embedded application Embedded computers Monocular vision Parallelizations Unmanned air vehicles Visual localization Stereo vision |
| description |
When targeting embedded applications such as on-board visual localization for small Unmanned Air Vehicles (UAV), available hardware generally becomes a limiting factor. For this reason, the usual strategy is to rely on pure motion integration and/or restricting the size of the map, i.e. performing visual odometry. Moreover, if monocular vision is employed, due to the additional computational cost of stereo vision, this requires dealing with the problem of unknown scale. In this work we discuss how the cost of the tracking task can be reduced without limiting the size of the global map. To do so, the notion of covisibility is strongly used which allows choosing a fixed and optimal set of points to be tracked. Moreover, this work delves into the concept of parallel tracking and mapping and presents some finer parallelization opportunities. Finally, we show how these strategies improve the computational times of a stereo visual SLAM framework called S-PTAM running on-board an embedded computer, close to camera frame-rates and with negligible precision loss. © 2017 IEEE. |
| format |
CONF |
| author |
Nitsche, M.A. Castro, G.I. Pire, T. Fischer, T. De Cristoforis, P. |
| author_facet |
Nitsche, M.A. Castro, G.I. Pire, T. Fischer, T. De Cristoforis, P. |
| author_sort |
Nitsche, M.A. |
| title |
Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| title_short |
Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| title_full |
Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| title_fullStr |
Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| title_full_unstemmed |
Constrained-covisibility marginalization for efficient on-board stereo SLAM |
| title_sort |
constrained-covisibility marginalization for efficient on-board stereo slam |
| url |
http://hdl.handle.net/20.500.12110/paper_97815386_v_n_p_Nitsche |
| work_keys_str_mv |
AT nitschema constrainedcovisibilitymarginalizationforefficientonboardstereoslam AT castrogi constrainedcovisibilitymarginalizationforefficientonboardstereoslam AT piret constrainedcovisibilitymarginalizationforefficientonboardstereoslam AT fischert constrainedcovisibilitymarginalizationforefficientonboardstereoslam AT decristoforisp constrainedcovisibilitymarginalizationforefficientonboardstereoslam |
| _version_ |
1782029606915670016 |