Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Mechanical Engineering | en_US |
| dc.contributor.advisor | Chu, Henry (ME) | en_US |
| dc.creator | Chen, Jiacong | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/12427 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | VIO-UWB loose coupling using weighted Kalman filter fusion algorithm | en_US |
| dcterms.abstract | In recent years, a variety of mobile robots have appeared in front of people, they can facilitate people's lives, and can also replace people to complete some high-risk tasks, and one of the core algorithms of such robots is based on Simultaneous positioning and mapping. Since the RGB-D camera can directly measure the depth information of image pixels, the depth calculation process of visual SLAM becomes simple and can be directly used for the construction of dense point cloud maps in indoor environments, which can effectively improve the accuracy and Robustness of visual SLAM systems. However, due to the defects of the visual sensor itself, it cannot effectively extract image features in weak texture and violent motion scenes, resulting in loss of tracking. The Inertial Measurement Unit (IMU) has a better estimation value when moving rapidly, which can make up for the lack of visual sensors. This SLAM algorithm is called visual-inertial odometry（VIO）. Even though state-of-the art methods such as [1]– [3] can achieve very accurate and high-rate pose and velocity estimates, sensor noise, and computation errors make the system prone to accumulated drift over time. Ultra-wideband technology is a wireless carrier communication technology, which has the advantages of low system complexity, low power spectral density of transmitted signals, insensitivity to channel fading, low interception capability, and high positioning accuracy. It is especially suitable for high-speed wireless access in dense multi-path places such as indoors. This paper studies the SLAM technology of indoor mobile robots based on the method of fusion of vision and inertia and proposes a high-precision and robust real-time Camera-IMU-UWB SLAM system. | en_US |
| dcterms.extent | 115 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2022 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Mobile robots | en_US |
| dcterms.LCSH | Robots -- Control systems | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 6875.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 8.41 MB | Adobe PDF | View/Open |
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