Real-time visual SLAM on embedded platforms
ORB-SLAM2 is a visual based SLAM (Simultaneous Localization and Mapping) application that estimates the trajectory of a moving object and at the same time, creates a map of the environment. This allows for good indoor spatial tracking as well as movement tracking. However, the robustness of ORB-SLAM...
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| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2020
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/137898 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | ORB-SLAM2 is a visual based SLAM (Simultaneous Localization and Mapping) application that estimates the trajectory of a moving object and at the same time, creates a map of the environment. This allows for good indoor spatial tracking as well as movement tracking. However, the robustness of ORB-SLAM2 is degraded in the presence of moving objects in the scene as the pixels that are selected for referencing between image frames may belong to these dynamic objects. This problem can be mitigated by using semantic segmentation to distinguish between static and dynamic objects in the scene and allow only the pixels of static objects to be used for referencing between image frames. The purpose of this report is to evaluate the performance of combining ORB-SLAM2 and semantic segmentation on an embedded platform. |
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