A Semantic SLAM Integrated with Enhanced YOLOv7 Target Detection Algorithm.
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| Title: | A Semantic SLAM Integrated with Enhanced YOLOv7 Target Detection Algorithm. |
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| Authors: | ZhangFang Hu1 3565207151@qq.com, FangYu Li2 s220431046@stu.cqupt.edu.cn, JiXiang Shen2 s220432006@stu.cqupt.edu.cn |
| Source: | Engineering Letters. Oct2024, Vol. 32 Issue 10, p1909-1920. 12p. |
| Subjects: | Image intensifiers, Camera movement, Robot motion, Dynamical systems, Algorithms |
| Abstract: | This paper proposes a semantic SLAM integrated with an enhanced YOLOv7 target detection algorithm. To address the issue of image blurring caused by robot movement and camera shake, we have incorporated an image enhancement module before the tracking thread. Consequently, the resulting images are more clearer. In the feature extraction stage, we introduce adaptive thresholds to improve the system's capability in feature point extraction. To minimize the influence of dynamic objects on this system, we employ an enhanced YOLOv7 algorithm to detect dynamic targets. Then, we integrate it with epipolar constraint to eliminate dynamic feature points. Finally, We evaluated our system with five sequences taken from the TUM dataset, and compared with ORB-SLAM3, our system improves more than 91% in accuracy, up to 98%. Moreover, compared to similar semantic SLAM systems, our system offers improved accuracy as well as enhanced real-time performance. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 181178660 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Semantic SLAM Integrated with Enhanced YOLOv7 Target Detection Algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22ZhangFang+Hu%22">ZhangFang Hu</searchLink><relatesTo>1</relatesTo><i> 3565207151@qq.com</i><br /><searchLink fieldCode="AR" term="%22FangYu+Li%22">FangYu Li</searchLink><relatesTo>2</relatesTo><i> s220431046@stu.cqupt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22JiXiang+Shen%22">JiXiang Shen</searchLink><relatesTo>2</relatesTo><i> s220432006@stu.cqupt.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering+Letters%22">Engineering Letters</searchLink>. Oct2024, Vol. 32 Issue 10, p1909-1920. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+intensifiers%22">Image intensifiers</searchLink><br /><searchLink fieldCode="DE" term="%22Camera+movement%22">Camera movement</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+motion%22">Robot motion</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper proposes a semantic SLAM integrated with an enhanced YOLOv7 target detection algorithm. To address the issue of image blurring caused by robot movement and camera shake, we have incorporated an image enhancement module before the tracking thread. Consequently, the resulting images are more clearer. In the feature extraction stage, we introduce adaptive thresholds to improve the system's capability in feature point extraction. To minimize the influence of dynamic objects on this system, we employ an enhanced YOLOv7 algorithm to detect dynamic targets. Then, we integrate it with epipolar constraint to eliminate dynamic feature points. Finally, We evaluated our system with five sequences taken from the TUM dataset, and compared with ORB-SLAM3, our system improves more than 91% in accuracy, up to 98%. Moreover, compared to similar semantic SLAM systems, our system offers improved accuracy as well as enhanced real-time performance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1909 Subjects: – SubjectFull: Image intensifiers Type: general – SubjectFull: Camera movement Type: general – SubjectFull: Robot motion Type: general – SubjectFull: Dynamical systems Type: general – SubjectFull: Algorithms Type: general Titles: – TitleFull: A Semantic SLAM Integrated with Enhanced YOLOv7 Target Detection Algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: ZhangFang Hu – PersonEntity: Name: NameFull: FangYu Li – PersonEntity: Name: NameFull: JiXiang Shen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 1816093X Numbering: – Type: volume Value: 32 – Type: issue Value: 10 Titles: – TitleFull: Engineering Letters Type: main |
| ResultId | 1 |
