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摘要:
The recent advances in sensing and display technologies have been transforming our living environments drastically. In this paper, a new technique is introduced to accurately reconstruct indoor environments in three-dimensions using a mobile platform. The system incorporates 4 ultrasonic sensors scanner system, an HD web camera as well as an inertial measurement unit (IMU). The whole platform is mountable on mobile facilities, such as a wheelchair. The proposed mapping approach took advantage of the precision of the 3D point clouds produced by the ultrasonic sensors system despite their scarcity to help build a more definite 3D scene. Using a robust iterative algorithm, it combined the structure from motion generated 3D point clouds with the ultrasonic sensors and IMU generated 3D point clouds to derive a much more precise point cloud using the depth measurements from the ultrasonic sensors. Because of their ability to recognize features of objects in the targeted scene, the ultrasonic generated point clouds performed feature extraction on the consecutive point cloud to ensure a perfect alignment. The range measured by ultrasonic sensors contributed to the depth correction of the generated 3D images (the 3D scenes). Experiments revealed that the system generated not only dense but precise 3D maps of the environments. The results showed that the designed 3D modeling platform is able to help in assistive living environment for self-navigation, obstacle alert, and other driving assisting tasks.
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文献信息
篇名 Indoor 3D Reconstruction Using Camera, IMU and Ultrasonic Sensors
来源期刊 传感技术(英文) 学科 工学
关键词 3D Point Cloud Position Estimation Iterative Closest Point (ICP) Ultrasonic Sensors Distance Measurement 3D Indoor Reconstruction
年,卷(期) 2020,(2) 所属期刊栏目
研究方向 页码范围 15-30
页数 16页 分类号 TP3
字数 语种
DOI
五维指标
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研究主题发展历程
节点文献
3D
Point
Cloud
Position
Estimation
Iterative
Closest
Point
(ICP)
Ultrasonic
Sensors
Distance
Measurement
3D
Indoor
Reconstruction
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
传感技术(英文)
季刊
2161-122X
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
114
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0
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0
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