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Research on Map-SLAM Fusion Localization Algorithm for Unmanned Vehicle
| Content Provider | MDPI |
|---|---|
| Author | Li, Shuguang Li, Zhenxu Liu, Xinxin Shan, Chunxiang Zhao, Yang Cheng, Hong |
| Copyright Year | 2022 |
| Description | Visionbased localization techniques and detection technologies are key algorithms for the localization and navigation of unmanned vehicles. Especially in scenarios where GPS signals are missing, Simultaneous Localization and Mapping (SLAM) techniques that rely on vision, inertial navigation system (INS) and other sensors have important applications. Among them, vision combined with the IMU SLAM system has the advantage of realistic scale, which is lacking in monocular vision and computational power compared to multivisual vision, so it is suitable for application in an unmanned vehicle system. In this paper, we propose a fusion localization algorithm that combines a visual-inertial SLAM system and map road information, processing road information in a map under structured roads, and detecting lane lines and locating its local position by a monocular camera, applying a strategy of position prediction and update for mapSLAM fusion localization. It solves the problem of accumulating errors in a pure SLAM system without loopback and provides accurate global-local positioning results for unmanned vehicle positioning and navigation. |
| Starting Page | 8670 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app12178670 |
| Journal | Applied Sciences |
| Issue Number | 17 |
| Volume Number | 12 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-08-29 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Transportation Science and Technology Unmanned Vehicle Slam Visual Ins Fusion Map Localization |
| Content Type | Text |
| Resource Type | Article |
