Memory Management for Real-Time Appearance-Based Loop Closure Detection
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916332640927744 |
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| author | Labbé, Mathieu Michaud, François |
| author_facet | Labbé, Mathieu Michaud, François |
| contents | Loop closure detection is the process involved when trying to find a match between the current and a previously visited locations in SLAM. Over time, the amount of time required to process new observations increases with the size of the internal map, which may influence real-time processing. In this paper, we present a novel real-time loop closure detection approach for large-scale and long-term SLAM. Our approach is based on a memory management method that keeps computation time for each new observation under a fixed limit. Results demonstrate the approach's adaptability and scalability using four standard data sets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15890 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Memory Management for Real-Time Appearance-Based Loop Closure Detection Labbé, Mathieu Michaud, François Robotics Computer Vision and Pattern Recognition Loop closure detection is the process involved when trying to find a match between the current and a previously visited locations in SLAM. Over time, the amount of time required to process new observations increases with the size of the internal map, which may influence real-time processing. In this paper, we present a novel real-time loop closure detection approach for large-scale and long-term SLAM. Our approach is based on a memory management method that keeps computation time for each new observation under a fixed limit. Results demonstrate the approach's adaptability and scalability using four standard data sets. |
| title | Memory Management for Real-Time Appearance-Based Loop Closure Detection |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.15890 |