A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes
RGBD camera-based VSLAM (Visual Simultaneous Localization and Mapping) algorithm is usually applied to assist robots with real-time mapping. However, due to the limited measuring principle, accuracy, and distance of the equipped camera, this algorithm has typical disadvantages in the large and dynam...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6973790 |
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| author | Panlong Gu Fengyu Zhou Dianguo Yu Fang Wan Wei Wang Bangguo Yu |
| author_facet | Panlong Gu Fengyu Zhou Dianguo Yu Fang Wan Wei Wang Bangguo Yu |
| author_sort | Panlong Gu |
| collection | DOAJ |
| description | RGBD camera-based VSLAM (Visual Simultaneous Localization and Mapping) algorithm is usually applied to assist robots with real-time mapping. However, due to the limited measuring principle, accuracy, and distance of the equipped camera, this algorithm has typical disadvantages in the large and dynamic scenes with complex lightings, such as poor mapping accuracy, easy loss of robot position, and much cost on computing resources. Regarding these issues, this paper proposes a new method of 3D interior construction, which combines laser radar and an RGBD camera. Meanwhile, it is developed based on the Cartographer laser SLAM algorithm. The proposed method mainly takes two steps. The first step is to do the 3D reconstruction using the Cartographer algorithm and RGBD camera. It firstly applies the Cartographer algorithm to calculate the pose of the RGBD camera and to generate a submap. Then, a real-time 3D point cloud generated by using the RGBD camera is inserted into the submap, and the real-time interior construction is finished. The second step is to improve Cartographer loop-closure quality by the visual loop-closure for the sake of correcting the generated map. Compared with traditional methods in large-scale indoor scenes, the proposed algorithm in this paper shows higher precision, faster speed, and stronger robustness in such contexts, especially with complex light and dynamic objects, respectively. |
| format | Article |
| id | doaj-art-35e8b294f5484febb45de4adfec25c63 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-35e8b294f5484febb45de4adfec25c632025-02-03T01:05:08ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/69737906973790A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor ScenesPanlong Gu0Fengyu Zhou1Dianguo Yu2Fang Wan3Wei Wang4Bangguo Yu5School of Control Science and Engineering, Shandong University, Jinan250061, Shandong, ChinaSchool of Control Science and Engineering, Shandong University, Jinan250061, Shandong, ChinaInstitute of Technology, Qu Fu Normal University, Jining 276825, Shandong, ChinaSchool of Control Science and Engineering, Shandong University, Jinan250061, Shandong, ChinaFaculty of Computer Science and Technology, Qi Lu University of Technology, Jining 276825, Shandong, ChinaSchool of Control Science and Engineering, Shandong University, Jinan250061, Shandong, ChinaRGBD camera-based VSLAM (Visual Simultaneous Localization and Mapping) algorithm is usually applied to assist robots with real-time mapping. However, due to the limited measuring principle, accuracy, and distance of the equipped camera, this algorithm has typical disadvantages in the large and dynamic scenes with complex lightings, such as poor mapping accuracy, easy loss of robot position, and much cost on computing resources. Regarding these issues, this paper proposes a new method of 3D interior construction, which combines laser radar and an RGBD camera. Meanwhile, it is developed based on the Cartographer laser SLAM algorithm. The proposed method mainly takes two steps. The first step is to do the 3D reconstruction using the Cartographer algorithm and RGBD camera. It firstly applies the Cartographer algorithm to calculate the pose of the RGBD camera and to generate a submap. Then, a real-time 3D point cloud generated by using the RGBD camera is inserted into the submap, and the real-time interior construction is finished. The second step is to improve Cartographer loop-closure quality by the visual loop-closure for the sake of correcting the generated map. Compared with traditional methods in large-scale indoor scenes, the proposed algorithm in this paper shows higher precision, faster speed, and stronger robustness in such contexts, especially with complex light and dynamic objects, respectively.http://dx.doi.org/10.1155/2020/6973790 |
| spellingShingle | Panlong Gu Fengyu Zhou Dianguo Yu Fang Wan Wei Wang Bangguo Yu A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes Complexity |
| title | A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes |
| title_full | A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes |
| title_fullStr | A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes |
| title_full_unstemmed | A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes |
| title_short | A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes |
| title_sort | 3d reconstruction method using multisensor fusion in large scale indoor scenes |
| url | http://dx.doi.org/10.1155/2020/6973790 |
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