Visual-SLAM Classical Framework and Key Techniques: A Review
With the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoid...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/12/4582 |
| _version_ | 1827656648727986176 |
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| author | Guanwei Jia Xiaoying Li Dongming Zhang Weiqing Xu Haojie Lv Yan Shi Maolin Cai |
| author_facet | Guanwei Jia Xiaoying Li Dongming Zhang Weiqing Xu Haojie Lv Yan Shi Maolin Cai |
| author_sort | Guanwei Jia |
| collection | DOAJ |
| description | With the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoidance. This review starts with the development of SLAM (Simultaneous Localization and Mapping) and proceeds to a review of V-SLAM (Visual-SLAM) from its proposal to the present, with a summary of its historical milestones. In this context, the five parts of the classic V-SLAM framework—visual sensor, visual odometer, backend optimization, loop detection, and mapping—are explained separately. Meanwhile, the details of the latest methods are shown; VI-SLAM (Visual inertial SLAM) is reviewed and extended. The four critical techniques of V-SLAM and its technical difficulties are summarized as feature detection and matching, selection of keyframes, uncertainty technology, and expression of maps. Finally, the development direction and needs of the V-SLAM field are proposed. |
| first_indexed | 2024-03-09T22:32:19Z |
| format | Article |
| id | doaj.art-d825755dd96f4a87a4cb121d4f23033c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:32:19Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d825755dd96f4a87a4cb121d4f23033c2023-11-23T18:55:40ZengMDPI AGSensors1424-82202022-06-012212458210.3390/s22124582Visual-SLAM Classical Framework and Key Techniques: A ReviewGuanwei Jia0Xiaoying Li1Dongming Zhang2Weiqing Xu3Haojie Lv4Yan Shi5Maolin Cai6School of Physics and Electronics, Henan University, Kaifeng 475004, ChinaSchool of Physics and Electronics, Henan University, Kaifeng 475004, ChinaSchool of Physics and Electronics, Henan University, Kaifeng 475004, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaSchool of Physics and Electronics, Henan University, Kaifeng 475004, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaWith the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoidance. This review starts with the development of SLAM (Simultaneous Localization and Mapping) and proceeds to a review of V-SLAM (Visual-SLAM) from its proposal to the present, with a summary of its historical milestones. In this context, the five parts of the classic V-SLAM framework—visual sensor, visual odometer, backend optimization, loop detection, and mapping—are explained separately. Meanwhile, the details of the latest methods are shown; VI-SLAM (Visual inertial SLAM) is reviewed and extended. The four critical techniques of V-SLAM and its technical difficulties are summarized as feature detection and matching, selection of keyframes, uncertainty technology, and expression of maps. Finally, the development direction and needs of the V-SLAM field are proposed.https://www.mdpi.com/1424-8220/22/12/4582visual-SLAMclassical frameworkkey techniquesdevelopmental needs |
| spellingShingle | Guanwei Jia Xiaoying Li Dongming Zhang Weiqing Xu Haojie Lv Yan Shi Maolin Cai Visual-SLAM Classical Framework and Key Techniques: A Review Sensors visual-SLAM classical framework key techniques developmental needs |
| title | Visual-SLAM Classical Framework and Key Techniques: A Review |
| title_full | Visual-SLAM Classical Framework and Key Techniques: A Review |
| title_fullStr | Visual-SLAM Classical Framework and Key Techniques: A Review |
| title_full_unstemmed | Visual-SLAM Classical Framework and Key Techniques: A Review |
| title_short | Visual-SLAM Classical Framework and Key Techniques: A Review |
| title_sort | visual slam classical framework and key techniques a review |
| topic | visual-SLAM classical framework key techniques developmental needs |
| url | https://www.mdpi.com/1424-8220/22/12/4582 |
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