3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM
In order to accomplish the automatic mobile mapping task in a small area of interest, a low cost UAV system is proposed in this paper. Multiple sensors including a global shutter camera and an inertial measurement unit are calibrated and synchronized to collect data from the area of interest. Firs...
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-6494ac21090d4b1c853c263a2a67780c2020-11-24T21:47:59ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-11-01XLII-2-W812713210.5194/isprs-archives-XLII-2-W8-127-20173D MOBILE MAPPING WITH A LOW COST UAV SYSTEMJ. Li0B. Yang1W. Wu2W. Dai3C. Chen4X. Zou5M. Tian6State Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaState Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, PR ChinaIn order to accomplish the automatic mobile mapping task in a small area of interest, a low cost UAV system is proposed in this paper. Multiple sensors including a global shutter camera and an inertial measurement unit are calibrated and synchronized to collect data from the area of interest. First the images are matched by the chronological order and the SfM is utilized. Then the origin SfM result is integrated with the IMU data by adding the IMU constraints into the bundle adjustment. At last the photogrammetry point clouds are generated using PMVS according to the extrinsic parameters. Experiments are undertaken in a typical scene with photogrammetry point clouds generated. The trajectory estimated by the proposed integration method are compared with the method that relies on image only, showing that the proposed method has better performance.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W8/127/2017/isprs-archives-XLII-2-W8-127-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. Li B. Yang W. Wu W. Dai C. Chen X. Zou M. Tian |
spellingShingle |
J. Li B. Yang W. Wu W. Dai C. Chen X. Zou M. Tian 3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
J. Li B. Yang W. Wu W. Dai C. Chen X. Zou M. Tian |
author_sort |
J. Li |
title |
3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM |
title_short |
3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM |
title_full |
3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM |
title_fullStr |
3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM |
title_full_unstemmed |
3D MOBILE MAPPING WITH A LOW COST UAV SYSTEM |
title_sort |
3d mobile mapping with a low cost uav system |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2017-11-01 |
description |
In order to accomplish the automatic mobile mapping task in a small area of interest, a low cost UAV system is proposed in this paper.
Multiple sensors including a global shutter camera and an inertial measurement unit are calibrated and synchronized to collect data
from the area of interest. First the images are matched by the chronological order and the SfM is utilized. Then the origin SfM result
is integrated with the IMU data by adding the IMU constraints into the bundle adjustment. At last the photogrammetry point clouds are
generated using PMVS according to the extrinsic parameters. Experiments are undertaken in a typical scene with photogrammetry
point clouds generated. The trajectory estimated by the proposed integration method are compared with the method that relies on image
only, showing that the proposed method has better performance. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W8/127/2017/isprs-archives-XLII-2-W8-127-2017.pdf |
work_keys_str_mv |
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1725894117650595840 |