Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM
This paper estimates the pose of a noncooperative space target utilizing a direct method of monocular visual simultaneous location and mapping (SLAM). A Large Scale Direct SLAM (LSD-SLAM) algorithm for pose estimation based on photometric residual of pixel intensities is provided to overcome the lim...
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Online Access: | http://dx.doi.org/10.1155/2019/9086891 |
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doaj-b43e183ef1104a90a52b2bcdc981cd532020-11-25T01:53:41ZengHindawi LimitedInternational Journal of Aerospace Engineering1687-59661687-59742019-01-01201910.1155/2019/90868919086891Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAMTing Lei0Xiao-Feng Liu1Guo-Ping Cai2Yun-Meng Liu3Pan Liu4Department of Engineering Mechanics, State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, ChinaDepartment of Engineering Mechanics, State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, ChinaDepartment of Engineering Mechanics, State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, ChinaShanghai Institute of Technical Physics of the Chinese Academy of Science, Shanghai 200083, ChinaShanghai Institute of Technical Physics of the Chinese Academy of Science, Shanghai 200083, ChinaThis paper estimates the pose of a noncooperative space target utilizing a direct method of monocular visual simultaneous location and mapping (SLAM). A Large Scale Direct SLAM (LSD-SLAM) algorithm for pose estimation based on photometric residual of pixel intensities is provided to overcome the limitation of existing feature-based on-orbit pose estimation methods. Firstly, new sequence images of the on-orbit target are continuously inputted, and the pose of each current frame is calculated according to minimizing the photometric residual of pixel intensities. Secondly, frames are distinguished as keyframes or normal frames according to the pose relationship, and these frames are used to optimize the local map points. After that, the optimized local map points are added to the back-end map. Finally, the poses of keyframes are further enumerated and optimized in the back-end thread based on the map points and the photometric residual between the keyframes. Numerical simulations and experiments are carried out to prove the validity of the proposed algorithm, and the results elucidate the effectiveness of the algorithm in estimating the pose of the noncooperative target.http://dx.doi.org/10.1155/2019/9086891 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ting Lei Xiao-Feng Liu Guo-Ping Cai Yun-Meng Liu Pan Liu |
spellingShingle |
Ting Lei Xiao-Feng Liu Guo-Ping Cai Yun-Meng Liu Pan Liu Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM International Journal of Aerospace Engineering |
author_facet |
Ting Lei Xiao-Feng Liu Guo-Ping Cai Yun-Meng Liu Pan Liu |
author_sort |
Ting Lei |
title |
Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM |
title_short |
Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM |
title_full |
Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM |
title_fullStr |
Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM |
title_full_unstemmed |
Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM |
title_sort |
pose estimation of a noncooperative target based on monocular visual slam |
publisher |
Hindawi Limited |
series |
International Journal of Aerospace Engineering |
issn |
1687-5966 1687-5974 |
publishDate |
2019-01-01 |
description |
This paper estimates the pose of a noncooperative space target utilizing a direct method of monocular visual simultaneous location and mapping (SLAM). A Large Scale Direct SLAM (LSD-SLAM) algorithm for pose estimation based on photometric residual of pixel intensities is provided to overcome the limitation of existing feature-based on-orbit pose estimation methods. Firstly, new sequence images of the on-orbit target are continuously inputted, and the pose of each current frame is calculated according to minimizing the photometric residual of pixel intensities. Secondly, frames are distinguished as keyframes or normal frames according to the pose relationship, and these frames are used to optimize the local map points. After that, the optimized local map points are added to the back-end map. Finally, the poses of keyframes are further enumerated and optimized in the back-end thread based on the map points and the photometric residual between the keyframes. Numerical simulations and experiments are carried out to prove the validity of the proposed algorithm, and the results elucidate the effectiveness of the algorithm in estimating the pose of the noncooperative target. |
url |
http://dx.doi.org/10.1155/2019/9086891 |
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