Real-Time SLAM Based on Dynamic Feature Point Elimination in Dynamic Environment Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.1109/access.2023.3324146
Slam (simultaneous localization and mapping) play an important role in the field of artificial and driverless intelligence. A real-time dynamic visual SLAM algorithm based on an object detection network is proposed to address the robustness and camera localization accuracy issues caused by dynamic objects in indoor dynamic scenes. The YOLOv5s model, which has the smallest depth and feature map width in the YOLOv5 series, is chosen as the object detection network. The backbone network is replaced with the lightweight ShuffleNetv2 network. Experimental results on the VOC2007 dataset show that the YOLOv5-LITE model reduces the network parameters by 41.89% and speeds up the runtime by 39.00% compared to the YOLOv5s model. A motion level division strategy is adopted to provide prior information to the object detection network. In the tracking thread of the visual SLAM system, a parallel thread combining the improved object detection network and multi-view geometry is introduced to eliminate dynamic feature points. The experimental results demonstrate that in dynamic scenes, the proposed algorithm improves the camera localization accuracy by an average of 85.38% compared to ORB-SLAM2. Finally, experiments in a real environment are conducted to validate the effectiveness of the algorithm.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2023.3324146
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/10283827.pdf
- OA Status
- gold
- Cited By
- 7
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387587642
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387587642Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2023.3324146Digital Object Identifier
- Title
-
Real-Time SLAM Based on Dynamic Feature Point Elimination in Dynamic EnvironmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Ruizhen Gao, Ziheng Li, Junfu Li, Baihua Li, Jun Zhang, Jun LiuList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2023.3324146Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/10283827.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/10283827.pdfDirect OA link when available
- Concepts
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Computer science, Artificial intelligence, Computer vision, Robustness (evolution), Thread (computing), Simultaneous localization and mapping, Object detection, Feature (linguistics), Dynamic network analysis, Pattern recognition (psychology), Robot, Mobile robot, Operating system, Biochemistry, Chemistry, Gene, Philosophy, Computer network, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 5Per-year citation counts (last 5 years)
- References (count)
-
60Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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